Publications - Dana Nau

[426] R. Li, D. S. Nau, M. Roberts, and M. Fine-Morris. Automatically learning HTN methods from landmarks. In International Florida AI Research Soc. Conference (FLAIRS), May 2024. To appear.

[425] V. Hsiao, D. Nau, and R. Dechter. Surrogate Bayesian networks for approximating evolutionary games. In International Conference on Artificial Intelligence and Statistics (AISTATS), May 2024. To appear.

[424] X. Pan, V. Hsiao, D. S. Nau, and M. J. Gelfand. Explaining the evolution of gossip. Proc. National Academy of Science, Feb. 2024.

[423] S. Patra, P. Rademacher, K. Jacobson, K. Hassold, O. Kulaksızoğlu, L. Hiatt, M. Roberts, and D. Nau. Relating goal and environmental complexity for improved task transfer: Initial results. In NeurIPS GenPlan Workshop, Dec. 2023.

[422] P. Zaidins, M. Roberts, and D. Nau. Implicit dependency detection for HTN plan repair. In ICAPS Workshop on Hierarchical Planning (HPlan), July 2023.

[421] V. Hsiao, D. Nau, and R. Dechter. Graph neural networks for dynamic abstraction sampling. In AAAI Workshop on Graphs and More Complex Structures for Learning and Reasoning (GCLR), Feb. 2023.

[420] R. Li, M. Roberts, D. Nau, and M. Fine-Morris. Teaching an HTN learner. In ICAPS Workshop on Hierarchical Planning (HPlan), June 2022.

[419] S. Patra, M. Cavolowsky, O. Kulaksizoglu, R. Li, L. M. Hiatt, M. Roberts, and D. Nau. A hierarchical goal-biased curriculum for training reinforcement learning. In International Florida AI Research Soc. Conference (FLAIRS), May 2022.

[418] V. Hsiao and D. Nau. A mean field game model of spatial evolutionary games. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2022.

[417] Y. Bansod, S. Patra, D. Nau, and M. Roberts. HTN replanning from the middle. In International Florida AI Research Soc. Conference (FLAIRS), May 2022.

[416] V. Hsiao, R. Dechter, and D. Nau. Fast Fourier transform reductions for Bayesian network inference. In International Conference on Artificial Intelligence and Statistics (AISTATS), Mar. 2022.

[415] S. Patra, J. Mason, M. Ghallab, D. Nau, and P. Traverso. Deliberative acting, planning and learning with hierarchical operational models. Artificial Intelligence 299:103523, Oct. 2021. Preprint available at Arxiv.

[414] D. Nau, S. Patra, M. Roberts, Y. Bansod, and R. Li. GTPyhop: A hierarchical goal+task planner implemented in Python. In ICAPS Workshop on Hierarchical Planning (HPlan), July 2021.

[413] R. Li, S. Patra, and D. Nau. Decentralized refinement planning and acting. In International Conference on Automated Planning and Scheduling (ICAPS), July 2021.

[412] Y. Bansod, D. S. Nau, S. Patra, and M. Roberts. Integrating planning and acting with a re-entrant HTN planner. In ICAPS Workshop on Hierarchical Planning (HPlan), July 2021.

[411] S. Patra, P. Traverso, M. Ghallab, and D. Nau. Coordination and control of hierarchically organized interacting agents. In International Florida AI Research Soc. Conference (FLAIRS), May 2021.

[410] V. Hsiao, X. Pan, D. Nau, and R. Dechter. Approximating spatial evolutionary games using Bayesian networks. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1533–1535, May 2021.

[409] S. Patra, A. Velasquez, M. Kang, and D. Nau. Using online planning and acting to recover from cyberattacks on software-defined networks. In Innovative Applications of AI Conference (IAAI), Feb. 2021.

[408] X. Pan, M. Gelfand, and D. Nau. Integrating evolutionary game theory and cross-cultural psychology to understand cultural change. American Psychologist 76(6):1054–1066, 2021.

[407] M. J. Gelfand, J. C. Jackson, X. Pan, D. Nau, D. Pieper, E. Denison, M. Dagher, P. A. M. Van Lange, C.-Y. Chiu, and M. Wang. The relationship between cultural tightness–looseness and COVID-19 cases and deaths: a global analysis. The Lancet Planetary Health 5(3):e135–e144, 2021.

[406] X. Pan, D. Nau, and M. Gelfand. Cooperative norms and the growth of threat: Differences across tight and loose cultures. In International Conference on Behavioural and Social Computing (BESC), Nov. 2020.

[405] S. Patra, J. Mason, A. Kumar, M. Ghallab, P. Traverso, and D. Nau. Integrating acting, planning, and learning in hierarchical operational models. In International Conference on Automated Planning and Scheduling (ICAPS), pp. 478–487, Oct. 2020. Best student paper honorable mention award.

[404] D. S. Nau. Temporal goal networks: Work in progress. In Z. Dannenhauer, M. Roberts, and T. Vaquero, editors, ICAPS 4th Integrated Execution (IntEx) and 8th Goal Reasoning (GR) Workshops, Oct. 2020. Invited talk.

[403] D. Nau and S. Patra. Integrated planning and acting using operational models. In M. Ghallab and M. Cashmore, editors, ICAPS Online Summer School on Automated Planning & Scheduling, Oct. 2020.

[402] R. Li, S. Patra, and D. Nau. Decentralized acting and planning using hierarchical operational models. In ICAPS Workshop on Distributed and Multi-Agent Planning (DMAP), Oct. 2020.

[401] X. Pan, D. Nau, S. De, and M. Gelfand. Threat and the evolution of tribalism. In International Association for Conflict Management (IACM) Conference, July 2020.

[400] S. Patra, M. Ghallab, D. Nau, and P. Traverso. APE: An acting and planning engine. Advances in Cognitive Systems 7, Dec. 2019.

[399] S. Patra, M. Ghallab, D. Nau, and P. Traverso. Interleaving acting and planning using operational models. In 3rd ICAPS Workshop on Integrated Planning, Acting, and Execution (IntEx 2019), pp. 46–54, July 2019.

[398] D. Nau, S. Patra, M. Ghallab, P. Traverso, and J. Mason. Hierarchical refinement as a generalization of HTN planning. In 2nd ICAPS Workshop on Hierarchical Planning, July 2019. Invited talk.

[397] S. Patra, P. Traverso, M. Ghallab, and D. Nau. Acting and planning using operational models. In AAAI Conference on Artificial Intelligence, 2019.

[396] P. Haslum, F. Ivankovic, M. Ramirez, D. Gordon, S. Thiébaux, V. Shivashankar, and D. S. Nau. Extending classical planning with state constraints: Heuristics and search for optimal planning. Journal of Artificial Intelligence Research 62:373–431, June 2018.

[395] I. Zuckerman, B. Wilson, and D. S. Nau. Avoiding game-tree pathology in two player adversarial search. Computational Intelligence 34(2):542–561, May 2018.

[394] S. Patra, P. Traverso, M. Ghallab, and D. Nau. Controller synthesis for hierarchical agent interactions. In Annual Conference on Advances in Cognitive Systems, 2018.

[393] S. Patra, M. Ghallab, D. Nau, and P. Traverso. Using operational models to integrate acting and planning. In ICAPS Workshop on Integrated Planning, Acting and Execution (IntEx), 2018.

[392] S. De, D. Nau, X. Pan, and M. Gelfand. Tipping points for norm change in human cultures. In SBP-BRIMS, 2018.

[391] K.-L. Cheng, I. Zuckerman, U. Kuter, and D. Nau. Modeling agent’s preferences by its designer’s social value orientation. Journal of Experimental and Theoretical Artificial Intelligence 30(2):257–277, 2018.

[390] D. S. Nau, M. Ghallab, and P. Traverso. Refinement planning and acting. In Conference on Advances in Cognitive Systems, May 2017. Invited talk.

[389] S. Patra, P. Traverso, M. Ghallab, and D. Nau. Planning and acting with hierarchical input/output automata. In ICAPS Workshop on Generalized Planning, 2017.

[388] S. De, M. Gelfand, and D. Nau. Understanding norm change: An evolutionary game-theoretic study. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2017. Extended version at https://www.cs.umd.edu/users/nau/papers/de2017understanding.pdf .

[387] M. Ghallab, D. S. Nau, and P. Traverso. Automated Planning and Acting. Cambridge University Press, Sept. 2016.

[386] M. J. Gelfand, P. Roos, D. Nau, J. Harrington, Y. Mu, and J. Jackson. Societal threat as a moderator of cultural group selection. Behavioral and Brain Sciences 39:e38, 2016. Commentary.

[385] S. De, M. J. Gelfand, D. Nau, and P. Roos. The inevitability of ethnocentrism revisited: Ethnocentrism diminishes as mobility increases. Scientific Reports 5(17963), Dec. 2015. Supplemental material.

[384] P. Roos, M. Gelfand, D. Nau, and J. Lun. Societal threat and cultural variation in strength of social norms: An evolutionary basis. Organizational Behavior and Human Decision Processes 129:14–23, July 2015. Supplemental material.

[383] D. Nau, M. Ghallab, and P. Traverso. Blended planning and acting: Preliminary approach, research challenges. In AAAI Conference on Artificial Intelligence, Jan. 2015.

[382] P. Traverso, M. Ghallab, and D. S. Nau. An IPC track on deliberative acting: Moving the competition ahead towards more relevant scientific challenges. In Workshop on the International Planning Competition (WIPC-15), p. 29, 2015.

[381] E. Raboin, P. Švec, D. S. Nau, and S. K. Gupta. Model-predictive asset guarding by team of autonomous surface vehicles in environment with civilian boats. Autonomous Robots 38(3):261–282, 2015.

[380] R. Alford, U. Kuter, D. S. Nau, and R. P. Goldman. Plan aggregation for strong-cyclic planning in nondeterministic domains. Artificial Intelligence 216:206–232, Nov. 2014.

[379] V. Shivashankar, K. N. Kaipa, D. S. Nau, and S. K. Gupta. Towards integrating hierarchical goal networks and motion planners to support planning for human-robot teams. In IROS Workshop on AI and Robotics, Sept. 2014.

[378] K.-L. Cheng, I. Zuckerman, D. Nau, and J. Golbeck. Predicting agents’ behavior by measuring their social preferences. In Eur. Conference on Artificial Intelligence (ECAI), Sept. 2014. Short paper.

[377] F. Ivankovic, P. Haslum, S. Thiebaux, V. Shivashankar, and D. Nau. Optimal planning with global numerical state constraints. In International Conference on Automated Planning and Scheduling (ICAPS), pp. 145–153, June 2014. Winner of the best student paper award.

[376] R. Alford, V. Shivashankar, U. Kuter, and D. S. Nau. On the feasibility of planning graph style heuristics for HTN planning. In International Conference on Automated Planning and Scheduling (ICAPS), June 2014.

[375] M. Ghallab, D. Nau, and P. Traverso. The actor’s view of automated planning and acting: A position paper. Artificial Intelligence 208:1–17, Mar. 2014.

[374] P. Roos, M. J. Gelfand, D. S. Nau, and R. Carr. High strength-of-ties and low mobility enable the evolution of third-party punishment. Proc. Royal Society B: Biological Sci. 281(1776), 7 Feb. 2014. Supplemental material.

[373] D. Nau. Integrated planning and acting: The actor’s view. In Conference on Advances in Cognitive Systems, Dec. 2013. Invited talk.

[372] V. Shivashankar, R. Alford, U. Kuter, and D. Nau. Hierarchical goal networks and goal-driven autonomy: Going where AI planning meets goal reasoning. In ACS Workshop on Goal Reasoning, pp. 95–110, 2013.

[371] V. Shivashankar, R. Alford, U. Kuter, and D. Nau. The GoDeL planning system: A more perfect union of domain-independent and hierarchical planning. In International Joint Conference on Artificial Intelligence (IJCAI), pp. 2380–2386, 2013.

[370] E. Raboin, P. Švec, D. S. Nau, and S. K. Gupta. Model-predictive target defense by team of unmanned surface vehicles operating in uncertain environments. In IEEE International Conference on Robotics and Automation (ICRA), 2013.

[369] D. Nau. Game applications of HTN planning with state variables. In ICAPS Workshop on Planning in Games, 2013. Invited talk.

[368] P. I. Cowling, M. Buro, M. Bida, A. Botea, B. Bouzy, M. V. Butz, P. Hingston, H. Muñoz-Avila, D. Nau, and M. Sipper. Search in real-time video games. In S. M. Lucas, M. Mateas, M. Preuss, P. Spronck, and J. Togelius, editors, Artificial and Computational Intelligence in Games, volume 6 of Dagstuhl Follow-Ups, chapter 1, pp. 21–32. Schloss Dagstuhl, 2013.

[367] D. Nau. What a long strange trip it’s been. In A Symposium in Honor of Professor Dana Nau, May 2012. Invited talk.

[366] V. Shivashankar, U. Kuter, D. S. Nau, and R. Alford. A hierarchical goal-based formalism and algorithm for single-agent planning. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 981–988, 2012.

[365] E. Raboin, D. Nau, and U. Kuter. Generating strategies for multi-agent pursuit-evasion games in partially observable Euclidean space (extended abstract). In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2012.

[364] E. Raboin, D. Nau, and U. Kuter. Generating strategies for multi-agent pursuit-evasion games in partially observable Euclidean space. In Autonomous Robots and Multirobot Systems (ARMS) Workshop, 2012.

[363] R. Carr, E. Raboin, A. Parker, and D. Nau. Theoretical and experimental analysis of an evolutionary social-learning game. Tech. Rep. CS-TR-5005, UMIACS-TR-2012-5, Department of Computer Science, University of Maryland, 2012.

[362] R. Alford, V. Shivashankar, U. Kuter, and D. S. Nau. HTN problem spaces: Structure, algorithms, termination. In International Symposium on Combinatorial Search (SoCS), 2012.

[361] V. Shivashankar, U. Kuter, and D. S. Nau. Hierarchical goal network planning: Initial results. Tech. Rep. CS-TR-4983, UMIACS-TR-2011-09, Department of Computer Science, University of Maryland, May 2011.

[360] B. Wilson, I. Zuckerman, and D. S. Nau. Modeling social preferences in multi-player games. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2011.

[359] V. Shivashankar, R. Jain, U. Kuter, and D. Nau. Real-time planning for covering an initially-unknown spatial environment. In International Florida AI Research Soc. Conference (FLAIRS), 2011.

[358] J. J. Salerno, S. J. Yang, D. S. Nau, and S.-K. Chai, editors. Social Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, volume 6589 of LNCS. Springer, 2011.

[357] K.-L. Cheng, I. Zuckerman, D. S. Nau, and J. Golbeck. The life game: Cognitive strategies for repeated stochastic games. In SocialCom/PASSAT, pp. 95–102, 2011.

[356] P. Roos, J. R. Carr, and D. S. Nau. Evolution of state-dependent risk preferences. ACM Transactions on Intelligent Systems and Technology (TIST) 1(1):6:1–6:21, Oct. 2010.

[355] H. Liu and D. Nau. Introduction to the ACM TIST special issue: AI in social computing and cultural modeling. ACM Trans. Intelligent Systems and Technology (TIST) 1(1):2:1–2:2, Oct. 2010.

[354] K.-L. Cheng, I. Zuckerman, U. Kuter, and D. Nau. Using a social orientation model for the evolution of cooperative societies. In 2010 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT-10), Sept. 2010.

[353] P. Roos and D. S. Nau. Risk preference and sequential choice in evolutionary games. Advances in Complex Systems 13(4):559–578, Aug. 2010.

[352] K.-L. Cheng, I. Zuckerman, U. Kuter, and D. S. Nau. Evolving cooperative societies. In Late Breaking abstracts workshop, Genetic and Evolutionary Computation Conference (GECCO’10), pp. 2067–2068, July 2010.

[351] K.-L. Cheng, I. Zuckerman, U. Kuter, and D. S. Nau. Emergence of cooperative societies in evolutionary games. In Fourth Evolutionary Computation and Multi-Agent Systems and Simulation Workshop (ECoMASS’10), pp. 1794–1800, July 2010.

[350] P. Roos and D. S. Nau. State-dependent risk preferences in evolutionary games. In S.-K. Chai, J. J. Salerno, and P. L. Mabry, editors, Advances in Social Computing: Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, volume LNCS 6007, pp. 23–31. Springer, Mar. 2010.

[349] E. Raboin, D. Nau, U. Kuter, S. K. Gupta, and P. Švec. Strategy generation in multi-agent imperfect-information pursuit games. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2010.

[348] A. Parker, D. S. Nau, and V. S. Subrahmanian. Paranoia versus overconfidence in imperfect-information games. In R. Dechter, H. Geffner, and J. Y. Halpern, editors, Heuristics, Probabilities, and Causality: A Tribute to Judea Pearl, pp. 63–87. College Publications, 2010.

[347] D. S. Nau, M. Luštrek, A. Parker, I. Bratko, and M. Gams. When is it better not to look ahead? Artificial Intelligence 174:1323–1338, 2010.

[346] P. Roos and D. S. Nau. Conditionally risky behavior vs expected value maximization in evolutionary games. In Sixth Conference of the European Social Simulation Association (ESSA 2009), Sept. 2009.

[345] D. S. Nau, U. Kuter, and E. Sefer. Thinking ahead in real-time search. In International Conference on Automated Planning and Scheduling (ICAPS), Sept. 2009.

[344] D. S. Nau. How do you plan if there are other agents and you don’t know their plans? In KI: Advances in AI (Annual German Conference on AI), Sept. 2009. Invited talk.

[343] D. S. Nau. Artificial intelligence and automation. In S. Y. Nof, editor, Springer Handbook of Automation, chapter 14. Springer-Verlag, Sept. 2009.

[342] B. Wilson, A. Parker, and D. S. Nau. Error minimizing minimax: Avoiding search pathology in game trees. In International Symposium on Combinatorial Search (SoCS), July 2009.

[341] E. Sefer, U. Kuter, and D. S. Nau. Real-time A* search with depth-k lookahead. In International Symposium on Combinatorial Search (SoCS), July 2009.

[340] R. Alford, U. Kuter, and D. S. Nau. Translating HTNs to PDDL: A small amount of domain knowledge can go a long way. In International Joint Conference on Artificial Intelligence (IJCAI), July 2009.

[339] R. Alford, U. Kuter, D. S. Nau, E. Reisner, and R. Goldman. Maintaining focus: Overcoming attention deficit disorder in contingent planning. In 22nd International Florida AI Research Soc. Conference (FLAIRS), May 2009.

[338] U. Kuter, D. S. Nau, M. Pistore, and P. Traverso. Task decomposition on abstract states, for planning under nondeterminism. Artificial Intelligence 173:669–695, 2009.

[337] R. Carr, E. Raboin, A. Parker, and D. Nau. Within epsilon of optimal play in the cultaptation social learning game. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2009. Extended abstract.

[336] R. Carr, E. Raboin, A. Parker, and D. Nau. Near-optimal play in a social learning game. In International Conference on Computational Cultural Dynamics (ICCCD), 2009.

[335] T.-C. Au, U. Kuter, and D. S. Nau. Planning for interactions among autonomous agents. In K. Hindriks, A. Pokahr, and S. Sardina, editors, ProMAS’08 Post-Proceedings. Springer, 2009. Invited paper.

[334] E. Raboin, R. Carr, A. Parker, and D. S. Nau. Balancing innovation and exploitation in a social learning game. In AAAI Fall Symposium on Adaptive Agents in Cultural Contexts, Nov. 2008.

[333] D. S. Nau. Learning how to behave in an unfamiliar society. In International Conference on Computational Cultural Dynamics (ICCCD), Sept. 2008. Invited talk.

[332] U. Kuter, D. S. Nau, E. Reisner, and R. Goldman. Using classical planners to solve nondeterministic planning problems. In International Conference on Automated Planning and Scheduling (ICAPS), pp. 190–197, Sept. 2008.

[331] A. Gerevini, U. Kuter, D. S. Nau, A. Saetti, and N. Waisbrot. Combining domain-independent planning and HTN planning: The Duet planner. In Workshop on Knowledge Engineering for Planning and Scheduling (KEPS), Sept. 2008.

[330] R. Carr, E. Raboin, A. Parker, and D. S. Nau. When innovation matters: An analysis of innovation in a social learning game. In International Conference on Computational Cultural Dynamics (ICCCD), Sept. 2008.

[329] D. S. Nau and J. Wilkenfeld. Computational cultural dynamics. IEEE Intelligent Systems 23(4):18–19, July-Aug. 2008.

[328] A. Gerevini, U. Kuter, D. S. Nau, A. Saetti, and N. Waisbrot. Combining domain-independent planning and HTN planning: The Duet planner. In Eur. Conference on Artificial Intelligence (ECAI), pp. 573–577, July 2008.

[327] D. S. Nau. Planning for interactions among autonomous agents. In Sixth International Workshop on Programming Multi-Agent Systems (ProMAS’08), May 2008. Invited talk.

[326] T.-C. Au, D. S. Nau, and S. Kraus. Synthesis of strategies from interaction traces. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 855–862, May 2008.

[325] S. Lee-Urban, H. Muñoz-Avila, A. Parker, U. Kuter, and D. S. Nau. Transfer learning of hierarchical task-network planning methods in a real-time strategy game. In Workshop on Artificial Intelligence Planning and Learning (AIPL-07), Sept. 2007.

[324] U. Kuter, D. S. Nau, E. Reisner, and R. Goldman. Conditionalization: Adapting forward-chaining planners to partially observable environments. In ICAPS 07 Workshop on Planning and Execution for Real-World Systems, Sept. 2007.

[323] D. S. Nau and J. Wilkenfeld, editors. First International Conference on Computational Cultural Dynamics. AAAI Press, Aug. 2007.

[322] T.-C. Au, S. Kraus, and D. S. Nau. Symbolic noise detection in the noisy iterated chicken game and the noisy iterated battle of the sexes. In International Conference on Computational Cultural Dynamics (ICCCD), Aug. 2007.

[321] D. S. Nau. May all your plans succeed! (or have a high expected utility). In Bar-Ilan Symposium on the Foundations of Artificial Intelligence (BISFAI), June 2007. Invited talk.

[320] V. S. Subrahmanian, M. Albanese, M. V. Martinez, D. S. Nau, D. Reforgiato, G. I. Simari, A. Sliva, O. Udrea, and J. Wilkenfeld. CARA: A cultural-reasoning architecture. IEEE Intelligent Systems 22(2):12–16, Mar./Apr. 2007.

[319] A. Parker, F. Yaman, D. S. Nau, and V. S. Subrahmanian. Probabilistic go theories. In International Joint Conference on Artificial Intelligence (IJCAI), pp. 501–506, 2007.

[318] D. S. Nau. Current trends in automated planning. AI Magazine 28(4):43–58, 2007.

[317] S. Khuller, V. Martinez, D. S. Nau, G. Simari, A. Sliva, and V. S. Subrahmanian. Finding most probable worlds of probabilistic logic programs. In International Conference on Scalable Uncertainty Management (SUM 2007), volume 4772 of LNCS, pp. 45–59, 2007.

[316] S. Khuller, M. V. Martinez, D. S. Nau, A. Sliva, G. I. Simari, and V. S. Subrahmanian. Computing most probable worlds of action probabilistic logic programs: scalable estimation for 1030,000 worlds. Annals of Math. and Artificial Intelligence 51(2-4):295–331, 2007.

[315] T.-C. Au and D. S. Nau. Reactive query policies: A formalism for planning with volatile external information. In IEEE Symposium on Computational Intelligence and Data Mining (CIDM), pp. 243–250, 2007.

[314] T.-C. Au and D. S. Nau. Is it accidental or intentional? A symbolic approach to the noisy iterated prisoner’s dilemma. In G. Kendall, X. Yao, and S. Y. Chong, editors, The Iterated Prisoners Dilemma: 20 Years On, pp. 231–262. World Scientific, 2007.

[313] T.-C. Au and D. S. Nau. The incompleteness of planning with volatile external information. In Eur. Conference on Artificial Intelligence (ECAI), pp. 839–840, Aug. 2006.

[312] A. Parker, D. S. Nau, and V. S. Subrahmanian. The role of imperfect information. In A. Kott and W. McEneaney, editors, Adversarial Reasoning: Computational Approaches to Reading the Opponent’s Mind, pp. 209–229. CRC Press, July 2006.

[311] A. Parker, D. S. Nau, and V. S. Subrahmanian. Overconfidence or paranoia? search in imperfect-information games. In National Conference on Artificial Intelligence, pp. 1045–1050, July 2006.

[310] T.-C. Au and D. S. Nau. Maintaining cooperation in noisy environments. In National Conference on Artificial Intelligence, pp. 1561–1564, July 2006.

[309] G. Simari, A. Sliva, V. Subrahmanian, and D. S. Nau. A stochastic language for modeling opponent agents. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 244–246, 2006.

[308] U. Kuter and D. S. Nau. Controlled search over compact state representations, in nondeterministic planning domains and beyond. In National Conference on Artificial Intelligence, pp. 1638–1641, 2006.

[307] O. Ilghami, D. S. Nau, and H. Munoz-Avila. Learning to do HTN planning. In International Conference on Automated Planning and Scheduling (ICAPS), pp. 390–393, 2006.

[306] T.-C. Au and D. S. Nau. Accident or intention: That is the question (in the iterated prisoner’s dilemma). In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 561–568, 2006.

[305] O. Ilghami, D. S. Nau, H. Muñoz-Avila, and D. W. Aha. Learning preconditions for planning from plan traces and HTN structure. Computational Intelligence 21(4):388–413, Nov. 2005.

[304] F. Yaman, D. S. Nau, and V. S. Subrahmanian. A motion closed world assumption. In International Joint Conference on Artificial Intelligence (IJCAI), pp. 621–626, Aug. 2005.

[303] F. Yaman, D. S. Nau, and V. S. Subrahmanian. Going far, logically. In International Joint Conference on Artificial Intelligence (IJCAI), pp. 615–620, Aug. 2005.

[302] A. Parker, D. S. Nau, and V. S. Subrahmanian. Game-tree search with combinatorially large belief states. In International Joint Conference on Artificial Intelligence (IJCAI), pp. 254–259, Aug. 2005.

[301] O. Ilghami, H. Muñoz-Avila, D. S. Nau, and D. W. Aha. Learning approximate preconditions for methods in hierarchical plans. In International Conference on Machine Learning (ICML), pp. 337–344, Aug. 2005.

[300] D. S. Nau. May all your plans succeed! In Twentieth National Conference on Artificial Intelligence, July 2005. Invited talk.

[299] U. Kuter and D. S. Nau. Using domain-configurable search control for probabilistic planning. In National Conference on Artificial Intelligence, pp. 1169–1174, July 2005.

[298] U. Kuter, D. S. Nau, M. Pistore, and P. Traverso. A hierarchical task-network planner based on symbolic model checking. In International Conference on Automated Planning and Scheduling (ICAPS), pp. 300–309, June 2005.

[297] D. S. Nau, T.-C. Au, O. Ilghami, U. Kuter, H. Muñoz-Avila, J. W. Murdock, D. Wu, and F. Yaman. Applications of SHOP and SHOP2. IEEE Intelligent Systems 20(2):34–41, Mar.-Apr. 2005.

[296] D. S. Nau, M. Fu, and V. S. Subrahmanian, editors. Workshop on Decision Making in Adversarial Domains, 2005. https://www.cs.umd.edu/projects/lccd/adversarial-2005.

[295] U. Kuter, E. Sirin, D. S. Nau, B. Parsia, and J. Hendler. Information gathering during planning for web service composition. Journal of Web Semantics 3(2-3):183–205, 2005.

[294] U. Kuter, J. Hu, D. S. Nau, M. Fu, and S. Marcus. Lower and upper bounds for action elimination in MDP planning problems. Tech. rep., University of Maryland, 2005.

[293] J. Dix, U. Kuter, and D. S. Nau. Planning in answer set programming using ordered task decomposition. In S. Artëmov, H. Barringer, L. Lamb, and J. Woods, editors, We Will Show Them! Essays in Honour of Dov Gabbay, Volume One, pp. 521–576. King’s College Publications, 2005.

[292] T.-C. Au and D. S. Nau. An analysis of derived belief strategy’s performance in the 2005 iterated prisoner’s dilemma competition. Tech. Rep. CSTR-4756/UMIACS-TR-2005-59, University of Maryland, College Park, 2005.

[291] T.-C. Au, U. Kuter, and D. S. Nau. Web service composition with volatile information. In International Semantic Web Conference (ISWC), pp. 52–66, 2005.

[290] E. Sirin, B. Parsia, D. Wu, J. Hendler, and D. S. Nau. HTN planning for web service composition using SHOP2. Journal of Web Semantics 1(4):377–396, Oct. 2004.

[289] U. Kuter, D. S. Nau, D. Gossink, and J. F. Lemmer. Interactive course-of-action planning using causal models. In Third International Conference on Knowledge Systems for Coalition Operations (KSCO-2004), pp. 37–52, Oct. 2004. (postponed).

[288] D. S. Nau and M. Ghallab. Measuring the performance of automated planning systems. In Performance Metrics for Intelligent Systems Workshop (PerMIS ’04), Aug. 2004.

[287] T.-C. Au, D. S. Nau, and V. S. Subrahmanian. Utilizing volatile external information during planning. In Eur. Conference on Artificial Intelligence (ECAI), pp. 647–651, Aug. 2004.

[286] U. Kuter and D. S. Nau. Forward-chaining planning in nondeterministic domains. In National Conference on Artificial Intelligence, pp. 513–518, July 2004.

[285] F. Yaman, D. S. Nau, and V. S. Subrahmanian. A logic of motion. In International Conference on Principles of Knowledge Representation and Reasoning (KR), pp. 85–94, June 2004.

[284] D. S. Nau, T.-C. Au, O. Ilghami, U. Kuter, H. Muñoz-Avila, J. W. Murdock, D. Wu, and F. Yaman. Applications of SHOP and SHOP2. Tech. Rep. CS-TR-4604, UMIACS-TR-2004-46, University of Maryland, June 2004. Revised December 2004.

[283] M. Ghallab, D. S. Nau, and P. Traverso. Automated Planning: Theory and Practice. Morgan Kaufmann, May 2004.

[282] F. Yaman, S. Adali, D. S. Nau, M. L. Sapino, and V.S.Subrahmanian. Plan databases: model and algebra. In Third International Symposium on Foundations of Information and Knowledge Systems (FoIKS), pp. 302–320, Feb. 2004.

[281] U. Kuter, E. Sirin, D. S. Nau, B. Parsia, and J. Hendler. Information gathering during planning for web services composition. In ICAPS-04 Workshop on Planning and Scheduling for Web and Grid Services, 2004.

[280] U. Kuter, E. Sirin, D. S. Nau, B. Parsia, and J. Hendler. Information gathering during planning for web service composition. In S. A. McIlraith, D. Plexousakis, and F. van Harmelen, editors, International Semantic Web Conference (ISWC), volume 3298 of LNCS, pp. 335–349. Springer-Verlag, 2004.

[279] U. Kuter, D. S. Nau, D. Gossink, and J. F. Lemmer. Interactive planning under uncertainty with causal modeling and analysis. In ICAPS-04 Workshop on Connecting Theory with Practice, 2004.

[278] E. Giunchiglia, N. Muscettola, and D. S. Nau. The 2003 International Conference on Automated Planning and Scheduling (ICAPS-03). AI Magazine 25(2):129–132, 2004.

[277] D. S. Nau, T.-C. Au, O. Ilghami, U. Kuter, J. W. Murdock, D. Wu, and F. Yaman. SHOP2: An HTN planning system. Journal of Artificial Intelligence Research 20:379–404, Dec. 2003.

[276] D. Wu, B. Parsia, E. Sirin, J. Hendler, and D. S. Nau. Automating DAML-S web services composition using SHOP2. In International Semantic Web Conference (ISWC), Nov. 2003.

[275] O. Ilghami and D. S. Nau. A general approach to synthesize problem-specific planners. Tech. Rep. CS-TR-4597, UMIACS-TR-2004-40, University of Maryland, Oct. 2003.

[274] J. Dix, U. Kuter, and D. S. Nau. Planning in answer set programming using ordered task decomposition. In B. N. A. Günther, R. Kruse, editor, KI 2003: Advances in Artificial Intelligence, volume 2821/2003 of LNAI, pp. 490–504. Springer, Sept. 2003.

[273] D. Wu, E. Sirin, J. Hendler, D. S. Nau, and B. Parsia. Automatic web services composition using SHOP2. In ICAPS Workshop on Planning for Web Services, June 2003.

[272] E. Giunchiglia, N. Muscettola, and D. S. Nau, editors. Proceedings of the Thirteenth International Conference on Automated Planning and Scheduling (ICAPS’03). AAAI Press, June 2003.

[271] D. Wu, E. Sirin, J. Hendler, D. S. Nau, and B. Parsia. Automatic web services composition using SHOP2. In Twelfth International World Wide Web Conference (WWW2003), May 2003. Poster.

[270] Z. Yao, S. K. Gupta, and D. S. Nau. Algorithms for selecting cutters in multi-part milling problems. Computer-Aided Design 35(9):824–838, 2003.

[269] T. McCluskey, D. Liu, and R. Simpson. GIPO II: HTN planning in a tool-supported knowledge engineering environment. In E. Guinchiglia, N. Muscettola, and D. Nau, editors, International Conference on Automated Planning and Scheduling (ICAPS), pp. 92–101, 2003.

[268] J. Dix, H. Muñoz-Avila, D. S. Nau, and L. Zhang. IMPACTing SHOP: Putting an AI planner into a multi-agent environment. Annals of Math. and Artificial Intelligence 37(4):381–407, 2003.

[267] T.-C. Au, H. Muñoz-Avila, and D. S. Nau. On the complexity of plan adaptation by derivational analogy in a universal classical planning framework. In S. Craw and A. Preece, editors, Eur. Conference on Case-Based Reasoning (ECCBR), pp. 13–27, Sept. 2002. Best research paper award.

[266] J. Dix, H. Muñoz-Avila, D. S. Nau, and L. Zhang. Planning in a multi-agent environment: Theory and practice. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 944–945. New York: ACM Press, July 2002.

[265] F. Yaman and D. S. Nau. Timeline: An HTN planner that can reason about time. In M. Fox and A. Coddington, editors, AIPS-2002 Workshop on Planning for Temporal Domains, 2002.

[264] D. Wu and D. S. Nau. UM-Translog-2: A planning domain designed for AIPS-2002. Tech. Rep. CS-TR-4402, UMIACS-TR-2002-82, University of Maryland, 2002.

[263] D. S. Nau, J. Meyer, M. Ball, J. Baras, A. Chowdhury, E. Lin, R. Rajamani, and V. Trichur. Integrated product and process design of microwave modules using AI planning and integer programming. In U. Cugini and M. Wozny, editors, Knowledge Intensive CAD, pp. 147–158. Kluwer Academic Publishers, 2002.

[262] D. S. Nau. Adversarial search. In Encyclopedia of Cognitive Science. Nature Publishing Group., 2002.

[261] H. Muñoz-Avila, K. Gupta, D. W. Aha, and D. S. Nau. Knowledge-based project planning. In R. Dieng-Kuntz and N. Matta, editors, Workshop on Knowledge Management and Organizational Memories. Kluwer Academic Publishers, 2002.

[260] O. Ilghami, D. S. Nau, H. Muñoz-Avila, and D. W. Aha. CaMeL: Learning method preconditions for HTN planning. In AIPS-2002, pp. 131–142, 2002.

[259] J. Dix, D. S. Nau, and U. Kuter. HTN planning in answer set programming. Tech. Rep. CS-TR-4336, Department of Computer Science, University of Maryland, 2002.

[258] J. Dix, H. Muñoz-Avila, D. S. Nau, and L. Zhang. Theoretical and empirical aspects of a planner in a multi-agent environment. In Eur. Conference Logics in Artificial Intelligence (JELIA), pp. 173–185, 2002.

[257] D. S. Nau, H. Muñoz-Avila, Y. Cao, A. Lotem, and S. Mitchell. Total-order planning with partially ordered subtasks. In International Joint Conference on Artificial Intelligence (IJCAI), pp. 425–430, Aug. 2001.

[256] H. Muñoz-Avila, K. Gupta, D. W. Aha, and D. S. Nau. Knowledge-based project planning. In IJCAI Workshop on Knowledge Management and Organizational Memories, Aug. 2001.

[255] H. Muñoz-Avila, D. W. Aha, D. S. Nau, R. Weber, L. Breslow, and F. Yaman. SiN: Integrating case-based reasoning with task decomposition. In International Joint Conference on Artificial Intelligence (IJCAI), Aug. 2001.

[254] Z. Yao, S. K. Gupta, and D. S. Nau. A geometric algorithm for selecting optimal set of cutters for multi-part milling. In ACM Symposium on Solid Modeling and Applications, June 2001.

[253] Z. Yao, S. K. Gupta, and D. S. Nau. A geometric algorithm for finding the largest milling cutter. Journal of Manufacturing Processes 3(1):1–16, 2001.

[252] T. Vossen, M. O. Ball, A. Lotem, and D. S. Nau. Applying integer programming to AI planning. Knowledge Engr. Review 16:85–100, 2001.

[251] D. S. Nau, Y. Cao, A. Lotem, and H. Muñoz-Avila. The SHOP planning system. AI Magazine, 2001.

[250] M. Ciocoiu, M. Gruninger, and D. S. Nau. Ontologies for integrating engineering applications. Journal of Computing and Information Science in Engineering 1(1):12–22, 2001.

[249] Z. Yao, S. K. Gupta, and D. S. Nau. Finding the maximal cutter for 2-d milling operations. In DETC 2000: 2000 ASME Design Engineering Technical Conference, Sept. 2000.

[248] J. Dix, H. Muñoz-Avila, and D. S. Nau. IMPACTing SHOP: Planning in a multi-agent environment. In F. Sadri and K. Satoh, editors, Second Workshop on Computational Logic and Multi-Agent Systems (CLIMA), pp. 30–42. Imperial College, July 2000.

[247] Z. Yao, S. K. Gupta, and D. S. Nau. A geometric algorithm for finding the maximal cutter for 2-d milling operations. In 10th International Conference on Flexible Automation and Intelligent Manufacturing, pp. 1105–1114, June 2000.

[246] D. S. Nau, Y. Cao, A. Lotem, and H. Muñoz-Avila. SHOP and M-SHOP: Planning with ordered task decomposition. Tech. Rep. CS TR 4157, University of Maryland, June 2000.

[245] A. Lotem and D. S. Nau. New advances in GraphHTN: Identifying independent subproblems in large HTN domains. In International Conference on Artificial Intelligence Planning Systems (AIPS), pp. 206–215, Apr. 2000.

[244] M. Ciocoiu and D. S. Nau. Ontology-based semantics. In International Conference on Principles of Knowledge Representation and Reasoning (KR), pp. 539–546, Apr. 2000.

[243] H. Muñoz-Avila, J. Dix, , D. S. Nau, and Y. Cao. Impacting SHOP: Foundations for integrating HTN planning and multi-agency. Tech. Rep. CS-TR-4100, Computer Science Department, University of Maryland, Feb. 2000.

[242] S. J. J. Smith and D. S. Nau. Competing approaches to computer bridge: Which is better? In H. J. v. d. Herik and H. Iida, editors, Games in AI Research, pp. 159–166. Universiteit Maastricht, 2000.

[241] D. S. Nau, J. Meyer, M. Ball, J. Baras, A. Chowdhury, E. Lin, R. Rajamani, and V. Trichur. Integrating AI planning and integer programming for use in integrated product and process design. In AAAI Workshop on Integration of AI and OR Techniques for Combinatorial Optimization. AAAI Press, 2000.

[240] D. S. Nau, J. Meyer, M. Ball, J. Baras, A. Chowdhury, E. Lin, R. Rajamani, and V. Trichur. Integrated product and process design of microwave modules using AI planning and integer programming. In Fourth Workshop on Knowledge Intensive CAD (KIC-4), pp. 186–196. IFIP Working Group 5.2, 2000.

[239] D. S. Nau, J. W. Herrmann, and W. C. Regli. Design classification and hybrid variant-generative process planning. In 2000 NSF Design and Manufacturing Research Conference, 2000.

[238] D. S. Nau, M. Ball, J. Baras, A. Chowdhury, E. Lin, J. Meyer, R. Rajamani, J. Splain, and V. Trichur. Generating and evaluating designs and plans for microwave modules. Artificial Intelligence for Engineering Design and Manufacturing 14:289–304, 2000.

[237] D. S. Nau, D. W. Aha, and H. Muñoz-Avila. Ordered task decomposition. In AAAI Workshop on Representational Issues for Real-World Planning Systems. AAAI Press, 2000.

[236] H. Muñoz-Avila, D. W. Aha, L. A. Breslow, D. S. Nau, and R. Weber. Integrating conversational case retrieval with generative planning. In Eur. Workshop on Case-Based Reasoning (EWCBR). Springer-Verlag, 2000.

[235] D. S. Nau, Y. Cao, A. Lotem, and H. Muñoz-Avila. SHOP: Simple hierarchical ordered planner. In T. Dean, editor, International Joint Conference on Artificial Intelligence (IJCAI), pp. 968–973. Morgan Kaufmann, Aug. 1999.

[234] T. Vossen, M. O. Ball, A. Lotem, and D. S. Nau. On the use of integer programming models in AI planning. In International Joint Conference on Artificial Intelligence (IJCAI), pp. 304–309, 1999.

[233] D. S. Nau. AI game-playing techniques: Are they useful for anything other than games? AI Magazine 20(1):117–118, 1999.

[232] H. Muñoz-Avila, D. McFarlane, D. W. Aha, J. Ballas, L. Breslow, and D. S. Nau. Using guidelines to constrain interactive case-based HTN planning. In International Conference on Case-Based Reasoning (ICCBR), pp. 288–302, 1999. Finalist for the best paper award.

[231] H. Muñoz-Avila, D. W. Aha, L. Breslow, and D. S. Nau. HICAP: an interactive case-based planning architecture and its application to noncombatant evacuation operations. In Innovative Applications of AI Conference (IAAI), pp. 870–875, 1999.

[230] A. Lotem, D. S. Nau, and J. Hendler. Using planning graphs for solving HTN problems. In National Conference on Artificial Intelligence, pp. 534–540, 1999.

[229] D. S. Nau and M. Sloan. Preface to flexibility in manufacturing: A proposal for study”. In 1998 Artificial Intelligence and Manufacturing: State of the Art and State of Practice, Sept. 1998.

[228] J. Meyer, M. O. Ball, J. Baras, A. Chowdhury, E. Lin, D. S. Nau, R. Rajamani, and V. Trichur. Process planning in microwave module production. In 1998 Artificial Intelligence and Manufacturing: State of the Art and State of Practice, Sept. 1998.

[227] T. Vossen, M. O. Ball, A. Lotem, and D. S. Nau. Integer programming models in AI planning: Preliminary experimental results. In AIPS’98 workshop on Planning as Combinatorial Search, June 1998.

[226] R. Tsuneto, J. Hendler, D. S. Nau, and L. d. Barros. Matching problem features with task selection for better performance in HTN planning. In AIPS Workshop on Knowledge Engineering and Acquisition for Planning, June 1998.

[225] R. Tsuneto, J. Hendler, and D. S. Nau. Analyzing external conditions to improve the efficiency of HTN planning. In National Conference on Artificial Intelligence, pp. 913–920, 1998.

[224] S. J. J. Smith, D. S. Nau, and T. Throop. Success in spades: Using AI planning techniques to win the world championship of computer bridge. In Innovative Applications of AI Conference (IAAI), pp. 1079–1086, 1998.

[223] S. J. J. Smith, D. S. Nau, and T. Throop. Computer bridge: A big win for AI planning. AI Magazine 19(2):93–105, 1998.

[222] D. S. Nau, S. J. J. Smith, and K. Erol. Control strategies in HTN planning: Theory versus practice. In Innovative Applications of AI Conference (IAAI), pp. 1127–1133, 1998.

[221] H. Muñoz-Avila, L. Breslow, D. W. Aha, and D. S. Nau. Description and functionality of NEODocTA. Tech. Rep. AIC-96-005, Naval Research Laboratory, Navy Center for Applied Research in Artificial Intelligence, 1998.

[220] J. W. Herrmann, I. Minis, D. S. Nau, K. Hebbar, and S. J. J. Smith. Integrated design and process planning for microwave modules. In J. M. Usher, U. Roy, and H. R. Parsaei, editors, Integrated Produce and Process Development: Methods, Tools, and Technologies, pp. 377–405. John Wiley & Sons, Inc., 1998.

[219] S. K. Gupta, D. S. Nau, and W. C. Regli. IMACS: A case study in real-world planning. IEEE Intelligent Systems 13(3):49–60, 1998.

[218] M. Ball, J. Baras, E. Lin, I. Minis, D. Nau, and R. Karne. Integrated product and process design tool for microwave modules. In 1998 NSF Design and Manufacturing Grantees Conference, pp. 655–656, 1998.

[217] R. Tsuneto, D. S. Nau, and J. Hendler. Plan-refinement strategies and search-space size. In Eur. Conference on Planning (ECP), Sept. 1997.

[216] D. S. Nau, S. Smith, and T. Throop. The Bridge Baron: A big win for AI planning. In Eur. Conference on Planning (ECP), Sept. 1997.

[215] A. Elinson, J. W. Herrmann, D. S. Nau, and G. Singh. Toward hybrid variant/generative process planning. In Proceedings of DETC’97: 1997 ASME Design Engineering Technical Conferences, Sept. 1997.

[214] A. Elinson, D. S. Nau, and W. C. Regli. Feature-based similarity assessment of solid models. In ACM Solid Modeling Conference, May 1997.

[213] K. Hebbar, I. Minis, S. J. J. Smith, and D. S. Nau. EDAPS: Integrated design and planning for electro-mechanical assemblies. In 1997 NSF Design and Manufacturing Grantees Conference, pp. 599–600, Jan. 1997.

[212] A. Elinson, D. S. Nau, and W. C. Regli. Classification and retrieval of CAD models using feature graphs. In 1997 NSF Design and Manufacturing Grantees Conference, pp. 141–142, Jan. 1997.

[211] S. J. J. Smith, K. Hebbar, D. S. Nau, and I. Minis. Integrating electrical and mechanical design and process planning. In M. Mantyla, S. Finger, and T. Tomiyama, editors, Knowledge Intensive CAD, Volume 2, pp. 269–288. Chapman and Hall, 1997.

[210] W. C. Regli, S. K. Gupta, and D. S. Nau. Towards multiprocessor feature recognition. Computer Aided Design 29(1):37–51, 1997.

[209] D. S. Nau, J. W. Herrmann, and W. C. Regli. Virtual factories for electro-mechanical device manufacturing. In EDS, editor, Global Virtual Manufacturing ’97, 1997. Tutorial.

[208] A. Mahanti, S. Ghosh, D. S. Nau, A. K. Pal, and L. N. Kanal. On the asymptotic performance of IDA*. Annals of Math. and Artificial Intelligence 20:161–193, 1997.

[207] S. K. Gupta, D. Das, W. C. Regli, and D. S. Nau. Automated manufacturability analysis: A survey. Research in Engineering Design 9(3):168–190, 1997.

[206] D. S. Nau. Commitment strategies in hierarchical task network planning. In Dagstuhl Meeting on Control of Search in AI Planning, Nov. 1996.

[205] V. S. Trichur, M. O. Ball, J. S. Baras, K. Hebbar, I. Minis, D. S. Nau, and S. J. Smith. Integrating tradeoff analysis and plan-based evaluation of designs for microwave modules. In Conference on Agile and Intelligent Manufacturing Systems, Oct. 1996.

[204] S. J. J. Smith, K. Hebbar, D. S. Nau, and I. Minis. Integrating electrical and mechanical design and process planning. In Second IFIP Workshop on Knowledge Intensive CAD, Sept. 1996.

[203] R. Tsuneto, K. Erol, J. Hendler, and D. S. Nau. Commitment strategies in hierarchical task network planning. In National Conference on Artificial Intelligence, Aug. 1996.

[202] S. J. J. Smith, D. S. Nau, and T. Throop. Total-order multi-agent task-network planning for contract bridge. In National Conference on Artificial Intelligence, Aug. 1996.

[201] D. S. Nau, R. Tsuneto, K. Erol, and J. Hendler. Search-space minimization for efficient refinement planning. In AAAI Workshop on Structural Issues in Planning and Temporal Reasoning, Aug. 1996.

[200] K. Hebbar, S. J. J. Smith, I. Minis, and D. S. Nau. Plan-based evaluation of designs for microwave modules. In ASME Design Technical Conference, Aug. 1996.

[199] E. Lin, I. Minis, D. S. Nau, and W. C. Regli. An assessment of virtual manufacturing technologies. In 1996 NSF Design and Manufacturing Grantees Conference, pp. 101–102, Jan. 1996.

[198] S. K. Gupta, W. C. Regli, D. S. Nau, and G. Zhang. IMACS (interactive manfacturability analysis and critiquing system). In 1996 NSF Design and Manufacturing Grantees Conference, pp. 131–132, Jan. 1996.

[197] S. J. J. Smith, D. S. Nau, and T. Throop. A planning approach to declarer play in contract bridge. Computational Intelligence 12(1):106–130, 1996.

[196] S. J. J. Smith, D. S. Nau, K. Hebbar, and I. Minis. Hierarchical task-network planning for process planning for manufacturing of microwave modules. In Artificial Intelligence and Manufacturing Research Planning Workshop, pp. 189–194. AAAI Press, 1996.

[195] S. Smith, D. S. Nau, and T. Throop. AI planning’s strong suit. IEEE Expert, 1996.

[194] M. Mantyla, D. S. Nau, and J. Shah. Challenges in feature-based manufacturing research. Communications of the ACM 39(2):77–85, 1996.

[193] S. Kambhampati and D. S. Nau. On the nature and role of modal truth criteria in planning. Artificial Intelligence 82(2), 1996.

[192] S. Ghosh, A. Mahanti, R. Nagi, and D. S. Nau. Manufacturing cell formation by state-space search. Annals of Operations Research 65:35–54, 1996.

[191] K. Erol, J. Hendler, and D. S. Nau. Complexity results for HTN planning. Annals of Math. and Artificial Intelligence 18:69–93, 1996.

[190] D. Das, S. K. Gupta, and D. S. Nau. Generating redesign suggestions to reduce setup cost: A step towards automated redesign. Computer Aided Design 28(10):763–782, 1996.

[189] W. C. Regli, J. Hendler, and D. S. Nau. Enabling technologies for automated redesign. In T. Tomiyama, M. Mantyla, and S. Finger, editors, Knowledge Intensive CAD-1: Preprints of the First IFIP WG 5.2 Workshop, pp. 455–463, Sept. 1995.

[188] W. C. Regli, S. K. Gupta, and D. S. Nau. Interactive feature recognition using multi-processor methods. In ASME Design Technical Conferences, pp. 927–937, Sept. 1995.

[187] W. C. Regli, J. Hendler, and D. S. Nau. Automating redesign of electro-mechanical assemblies. In IJCAI Workshop on Intelligent Manufacturing Systems, pp. 289–309, Aug. 1995.

[186] E. Lin, I. Minis, D. S. Nau, and W. C. Regli. Contribution to virtual manufacturing background research, phase ii. Tech. rep., University of Maryland, May 1995.

[185] E. Lin, I. Minis, D. S. Nau, and W. C. Regli. Contribution to virtual manufacturing background research. Tech. rep., University of Maryland, May 1995.

[184] G. Zhang, M. Woodruff, and D. S. Nau. Evaluation of computer generated process plans. In 1995 NSF Design and Manufacturing Grantees Conference, pp. 575–576, Jan. 1995.

[183] D. S. Nau, M. O. Ball, I. Minis, and G. Zhang. Virtual factories for electro-mechanical device manufacturing. In 1995 NSF Design and Manufacturing Grantees Conference, pp. 571–572, Jan. 1995.

[182] S. K. Gupta, D. S. Nau, and W. C. Regli. Systematically analyzing the manufacturability of machined parts. In 1995 NSF Design and Manufacturing Grantees Conference, pp. 107–108, Jan. 1995.

[181] V. S. Subrahmanian, D. S. Nau, and C. Vago. WFS + branch and bound = stable models. IEEE Transactions on on Knowledge and Data Engineering 7(3):362–377, 1995.

[180] W. C. Regli, S. K. Gupta, and D. S. Nau. Extracting alternative machining features: An algorithmic approach. Research in Engineering Design 7(3):173–192, 1995.

[179] W. C. Regli, S. K. Gupta, and D. S. Nau. An application of distributed solid modeling: Feature recognition. In ASME Design Technical Methods Conference, 1995.

[178] D. S. Nau, W. C. Regli, and S. K. Gupta. AI planning versus manufacturing-operation planning: A case study. In International Joint Conference on Artificial Intelligence (IJCAI), 1995.

[177] D. S. Nau, S. K. Gupta, and W. C. Regli. Manufacturing-operation planning versus AI planning. In AAAI Spring Symposium on Integrated Planning Applications, 1995.

[176] S. K. Gupta, W. C. Regli, and D. S. Nau. Manufacturing feature instances: Which ones to recognize? In ACM Solid Modeling Conference, 1995.

[175] S. K. Gupta and D. S. Nau. Systematic approach to analysing the manufacturability of machined parts. Computer Aided Design 27(5):323–342, 1995.

[174] S. K. Gupta, D. Das, W. C. Regli, and D. S. Nau. Current trends and future challenges in automated manufacturability analysis. In ASME Computers in Engineering Conference, pp. 655–665, 1995.

[173] M. Evett, J. Hendler, A. Mahanti, and D. S. Nau. PRA*: Massively parallel heuristic search. J of Parallel and Distributed Computing 25(2), 1995.

[172] K. Erol, D. S. Nau, and V. S. Subrahmanian. Complexity, decidability and undecidability results for domain-independent planning. Artificial Intelligence 76(1–2):75–88, 1995.

[171] K. Erol, J. Hendler, D. S. Nau, and R. Tsuneto. A critical look at critics in HTN planning. In International Joint Conference on Artificial Intelligence (IJCAI), 1995.

[170] D. Das, S. K. Gupta, and D. S. Nau. Estimation of setup time for machined parts: Accounting for work-holding constraints using a vise. In ASME Computers in Engineering Conference, pp. 619–631, 1995.

[169] W. C. Regli, S. K. Gupta, and D. S. Nau. Feature recognition for manufacturability analysis. In K. Ishii, editor, ASME Computers in Engineering Conference, pp. 93–104. ASME, Sept. 1994.

[168] K. Erol, J. Hendler, and D. S. Nau. UMCP: A sound and complete procedure for hierarchical task-network planning. In International Conference on Artificial Intelligence Planning Systems (AIPS), pp. 249–254, June 1994. Honorable mention for the 2009 ICAPS Influential Paper Award.

[167] K. Erol, J. Hendler, and D. S. Nau. Semantics for hierarchical task-network planning. Tech. Rep. CS TR-3239, UMIACS TR-94-31, ISR-TR-95-9, University of Maryland, Mar. 1994.

[166] G. Zhang, D. S. Nau, W. Ko, and S. K. Gupta. Economic evaluation of alternative machining operation plans. In 1994 NSF Design and Manufacturing Grantees Conference, pp. 397–398, Jan. 1994.

[165] W. C. Regli and D. S. Nau. Recognition of volumetric features from CAD models: A new approach. In 1994 NSF Design and Manufacturing Grantees Conference, pp. 745–746, Jan. 1994.

[164] S. K. Gupta, D. S. Nau, and G. Zhang. Systematically generating and evaluating alternative operation plans. In 1994 NSF Design and Manufacturing Grantees Conference, pp. 155–156, Jan. 1994.

[163] S. J. J. Smith and D. S. Nau. An analysis of forward pruning. In National Conference on Artificial Intelligence, 1994.

[162] K. Shim, T. Sellis, and D. S. Nau. Improvements on a heuristic algorithm for multiple-query optimization. Data and Knowledge Engineering 12(2):197–222, 1994.

[161] J. Shah, M. Mantyla, and D. S. Nau. Introduction to feature based manufacturing. In J. Shah, M. Mantyla, and D. S. Nau, editors, Advances in Feature Based Manufacturing, pp. 1–11. Elsevier/North Holland, 1994.

[160] J. Shah, M. Mantyla, and D. S. Nau, editors. Advances in Feature Based Manufacturing. Elsevier/North Holland, 1994.

[159] D. S. Nau, M. O. Ball, S. K. Gupta, I. Minis, and G. Zhang. Design for manufacture by multi-enterprise partnerships: Current status and future directions. In ASME Winter Annual Meeting, 1994.

[158] D. S. Nau, M. O. Ball, S. K. Gupta, I. Minis, and G. Zhang. Design for manufacture by multi-enterprise partnerships. In D. R. Rehak and J. H. Garrett, Jr., editors, Bridging the Generations: An International Workshop on the Future Directions of Computer-Aided Engineering, pp. 163–168, 1994.

[157] S. Kambhampati and D. S. Nau. On the nature of modal truth criteria in planning. In National Conference on Artificial Intelligence, 1994.

[156] S. K. Gupta, W. C. Regli, and D. S. Nau. Integrating DFM with CAD through design critiquing. Concurrent Engineering: Research and Applications 2(2), 1994. Special issue on AI in concurrent engineering.

[155] S. K. Gupta, D. S. Nau, W. C. Regli, and G. Zhang. A methodology for systematic generation and evaluation of alternative operation plans. In J. Shah, M. Mantyla, and D. S. Nau, editors, Advances in Feature Based Manufacturing, pp. 161–184. Elsevier/North Holland, 1994.

[154] S. K. Gupta, T. R. Kramer, D. S. Nau, W. C. Regli, and G. Zhang. Building MRSEV models for CAM applications. Advances in Engineering Software 20(2/3):121–139, 1994.

[153] S. Ghosh, A. Mahanti, and D. S. Nau. ITS: An efficient limited-memory heuristic tree search algorithm. In National Conference on Artificial Intelligence, pp. 1353–1358, 1994.

[152] S. Ghosh, A. Mahanti, and D. S. Nau. Improving the efficiency of limited-memory heuristic search. Tech. Rep. CS-TR-3420, UMIACS-TR-95-23, ISR-TR 95-35, University of Maryland, 1994.

[151] K. Erol, J. Hendler, and D. S. Nau. HTN planning: Complexity and expressivity. In National Conference on Artificial Intelligence, pp. 1123–1128, 1994.

[150] D. Das, S. K. Gupta, and D. S. Nau. Reducing setup cost by automated generation of redesign suggestions. In K. Ishii, editor, ASME Computers in Engineering Conference, pp. 159–170, 1994. Best-paper award winner.

[149] W. C. Regli and D. S. Nau. Building a general approach to feature recognition of material removal shape element volumes (MRSEVs). In J. Rossignac and J. Turner, editors, Second Symposium on Solid Modeling Foundations and CAD/CAM Applications. ACM SIGGRAPH, May 1993.

[148] S. K. Gupta and D. S. Nau. Generation of alternative feature-based models and precedence orderings for machining applications. In J. Rossignac and J. Turner, editors, Second Symposium on Solid Modeling Foundations and CAD/CAM Applications. ACM SIGGRAPH, May 1993.

[147] D. S. Nau. On the complexity of possible truth. In AAAI Spring Symposium, Apr. 1993.

[146] D. S. Nau. Enabling-condition interactions and finding good plans. In AAAI Spring Symposium, Apr. 1993.

[145] K. Erol, D. S. Nau, and V. S. Subrahmanian. A theoretical study of domain-independent planning. In AAAI Spring Symposium, Apr. 1993.

[144] K. Erol, D. S. Nau, and J. Hendler. Toward a general framework for hierarchical task-network planning. In AAAI Spring Symposium, Apr. 1993.

[143] D. S. Nau, J. Hendler, and Q. Yang. Merging plans efficiently. In 1993 NSF Design and Manufacturing Systems Grantees Conference, pp. 1809–1820, Jan. 1993.

[142] S. K. Gupta, D. S. Nau, and G. Zhang. Generation of machining alternatives for machinability evaluation. In 1993 NSF Design and Manufacturing Systems Grantees Conference, pp. 1771–1780, Jan. 1993.

[141] S. K. Gupta, D. S. Nau, and G. Zhang. Concurrent evaluation of machinability during product design. In Computer, volume 26, pp. 62–63, Jan. 1993.

[140] S. J. J. Smith and D. S. Nau. Toward an analysis of forward pruning. In Games: Planning and Learning, Papers from the 1993 Fall Symposium. AAAI Press, 1993.

[139] S. J. J. Smith and D. S. Nau. Strategic planning for imperfect-information games. In Games: Planning and Learning, Papers from the 1993 Fall Symposium. AAAI Press, 1993.

[138] W. C. Regli and D. S. Nau. Recognition of volumetric features from CAD models: Problem formalization and algorithms. Tech. Rep. ISR TR 93-41, University of Maryland, 1993.

[137] D. S. Nau, G. Zhang, S. K. Gupta, and R. Karinthi. Evaluating product machinability for concurrent engineeering. In W. G. Sullivan and H. R. Parsaei, editors, Concurrent Engineering: Contemporary Issues and Modern Design Tools, pp. 264–279. Chapman and Hall, 1993.

[136] D. S. Nau, S. K. Gupta, T. R. Kramer, W. C. Regli, and G. Zhang. Using MRSEVs to develop machining alternatives. In AAAI/SIGMAN Workshop on Intelligent Manufacturing, pp. 21–25, 1993.

[135] D. S. Nau, S. K. Gupta, T. R. Kramer, W. C. Regli, and G. Zhang. Development of machining alternatives, based on MRSEVs. In ASME Computers in Engineering Conference, 1993.

[134] D. S. Nau. State-space search, problem reduction, and iterative deepening: A comparative analysis. Tech. Rep. ISR TR 93-38, CS-TR-3053, UMIACS-TR-93-30, University of Maryland, 1993.

[133] D. S. Nau. On the nature of modal truth in plans. Tech. Rep. CS-TR-3031, UMIACS-TR-93-11, ISR TR 93-14, Institute for Systems Research, University of Maryland, 1993.

[132] S. Kambhampati and D. S. Nau. On the nature and role of the modal truth criteria in planning. Tech. Rep. ISR-TR-93-30, ISR, University of Maryland, 1993.

[131] S. K. Gupta, D. S. Nau, and G. Zhang. Interpreting product designs for manufacturability evaluation. In R. Gadh, editor, Intelligent Concurrent Design: Fundamentals, Methodology, Modeling, and Practice, volume DE-Vol. 66, pp. 33–43, 1993.

[130] S. K. Gupta, D. S. Nau, and G. Zhang. Estimation of achievable tolerances. Tech. Rep. TR-93-44, Institute for Systems Research, University of Maryland, 1993.

[129] Q. Yang, D. S. Nau, and J. Hendler. Merging separately generated plans with restricted interactions. Computational Intelligence 8(4):648–676, Nov. 1992.

[128] D. S. Nau, G. Zhang, and S. K. Gupta. Generation and evaluation of alternative operation sequences. In A. R. Thangaraj, A. Bagchi, M. Ajanappa, and D. K. Anand, editors, Quality Assurance through Integration of Manufacturing Processes and Systems, ASME Winter Annual Meeting, volume PED-Vol. 56, pp. 93–108, Nov. 1992.

[127] S. K. Gupta, D. S. Nau, G. Zhang, and T. R. Kramer. Feature algebra using PDES/STEP. In Second Workshop on Process Planning Concepts, Representations and Architectures, Aug. 1992.

[126] S. Blanksteen, J. Hendler, and D. S. Nau. The verification and validation of expert systems. In Total Quality Management: Metrics of Success III. Westinghouse Electronic Systems Group, Aug. 1992.

[125] A. Mahanti, D. S. Nau, S. Ghosh, A. K. Pal, and L. N. Kanal. Performance of IDA* on trees and graphs. In National Conference on Artificial Intelligence, pp. 539–544, July 1992.

[124] K. Erol, D. S. Nau, and V. S. Subrahmanian. On the complexity of domain-independent planning. In National Conference on Artificial Intelligence, pp. 381–386, July 1992.

[123] S. J. J. Smith, D. S. Nau, and T. Throop. A hierarchical approach to strategic planning with non-cooperating agents under conditions of uncertainty. In International Conference on Artificial Intelligence Planning Systems (AIPS), pp. 299–300, June 1992.

[122] K. Erol, D. S. Nau, and V. S. Subrahmanian. When is planning decidable? In International Conference on Artificial Intelligence Planning Systems (AIPS), pp. 222–227, June 1992.

[121] R. Karinthi, D. S. Nau, and Q. Yang. Handling feature interactions in process planning. Applied Artificial Intelligence 6(4):389–415, 1992. Special issue on AI for manufacturing.

[120] R. Karinthi and D. S. Nau. Geometric reasoning using a feature algebra. In F. Famili, D. S. Nau, and S. Kim, editors, Artificial Intelligence Applications in Manufacturing, pp. 41–59. AAAI Press/MIT Press, 1992.

[119] R. Karinthi and D. S. Nau. An algebraic approach to feature interactions. IEEE Trans. Pattern Analysis and Machine Intelligence 14(4):469–484, 1992.

[118] S. K. Gupta and D. S. Nau. Generation of alternative feature-based models and precedence orderings for machining applications. Tech. Rep. TR 92-111, Institute for Systems Research, University of Maryland, 1992.

[117] N. Gupta and D. S. Nau. On the complexity of blocks-world planning. Artificial Intelligence 56(2-3):223–254, 1992.

[116] F. Famili, D. S. Nau, and S. Kim, editors. Artificial Intelligence Applications in Manufacturing. AAAI Press/MIT Press, 1992.

[115] D. P. Eshner, J. Hendler, and D. S. Nau. Incremental planning using conceptual graphs. Journal of Experimental and Theoretical Artificial Intelligence 4:85–94, 1992.

[114] P.-C. Chi and D. S. Nau. In search of practical alternatives to minimax. In Conference Association of Asian-Pacific Operational Res. Societies (APORS), Aug. 1991.

[113] N. Gupta and D. S. Nau. Complexity results for blocks-world planning. In National Conference on Artificial Intelligence, pp. 629–633, July 1991. Honorable mention for the best paper award.

[112] A. Mahanti, A. K. Pal, S. Ghosh, L. Kanal, and D. S. Nau. Performance of A* and IDA*—a worst-case analysis. In 1991 ACM/IEEE Symposium on Applied Computing, Apr. 1991.

[111] D. S. Nau and R. Karinthi. Geometric reasoning for design and process planning. In 17th Annual NSF Conference on Design and Manufacturing Systems Research, Jan. 1991.

[110] Q. Yang, D. S. Nau, and J. Hendler. Merging separately generated plans with restricted interactions. Tech. Rep. CS-TR-2677, UMIACS-TR-91-73, University of Maryland, 1991.

[109] G. Vanecek, Jr., D. S. Nau, and R. Karinthi. A simple approach to performing set operations on polyhedra. Tech. Rep. SRC TR 91-34, University of Maryland, 1991.

[108] D. P. Eshner, J. Hendler, and D. S. Nau. Incremental planning using conceptual graphs. In Fifth Workshop on Conceptual Graphs, 1991.

[107] K. Erol, D. S. Nau, and V. S. Subrahmanian. Complexity, decidability and undecidability results for domain-independent planning: A detailed analysis. Tech. Rep. CS-TR-2797, UMIACS-TR-91-154, SRC-TR-91-96, Computer Science Department and Institute for Systems Research, University of Maryland, 1991.

[106] M. Ajanappa, J. A. Kirk, D. K. Anand, and D. S. Nau. Automated rapid prototyping with heuristics and intelligence: Part I—configuration. International Journal of Computer Integrated Manufacturing 4(4):219–231, 1991.

[105] R. Karinthi and D. S. Nau. Using a feature algebra in concurrent engineering design and manufacturing. In The Fifth International Conference on CAD/CAM, Robotics and Factories of the Future, Dec. 1990.

[104] M. Evett, J. Hendler, A. Mahanti, and D. S. Nau. PRA*: A memory-limited heuristic search procedure for the connection machine. In Frontiers of Massively Parallel Computation, Oct. 1990.

[103] D. S. Nau and R. Karinthi. Handling feature interactions in concurrent design and manufacturing. In Manufacturing International 1990, Aug. 1990.

[102] R. Karinthi and D. S. Nau. An approach to addressing geometric feature interactions in concurrent design. In Computers in Engineering 1990, volume 1, pp. 243–250, Aug. 1990.

[101] R. Karinthi and D. S. Nau. Using feature interactions in process planning. In SIGMAN Workshop on Manufacturing Planning and Control, July 1990.

[100] D. S. Nau and R. Karinthi. An approach to addressing geometric feature interactions in concurrent design. In Fourth Eurographics Workshop on Intelligent CAD Systems, Apr. 1990.

[99]  Q. Yang, D. S. Nau, and J. Hendler. Optimization of multiple-goal plans with limited interaction. In DARPA Workshop on Innovative Approaches to Planning, Scheduling and Control, 1990.

[98]  D. S. Nau, editor. Proceedings of the Second SIGMAN Workshop on Manufacturing Planning. Boston, MA, 1990.

[97]  R. Karinthi and D. S. Nau. Handling feature interactions using a feature algebra. In SIGMAN Workshop on Concurrent Engineering Design, 1990.

[96]  Q. Yang and D. S. Nau. Preprocessing search spaces for branch-and-bound search. In International Joint Conference on Artificial Intelligence (IJCAI), pp. 349–353, Aug. 1989.

[95]  Q. Yang and D. S. Nau. Optimization of multiple goal plans in automated manufacturing. In First SIGMAN Workshop on Manufacturing Planning, Aug. 1989.

[94]  R. Karinthi and D. S. Nau. Using a feature algebra for reasoning about geometric feature interactions. In International Joint Conference on Artificial Intelligence (IJCAI), Aug. 1989.

[93]  R. Karinthi and D. S. Nau. Geometric reasoning as a guide to process planning. In ASME Computers in Engineering Conference, Aug. 1989.

[92]  R. Karinthi and D. S. Nau. Algebraic feature translation and applications to concurrent design. In Workshop on Concurrent Engineering Design, Aug. 1989.

[91]  P.-C. Chi and D. S. Nau. Genetic algorithm and success rate optimization. In Beijing International Symposium for Young Computer Professionals, Aug. 1989.

[90]  Q. Yang, D. S. Nau, and J. Hendler. Exploiting limited interactions in plan optimization. Tech. Rep. CS-TR-2411, SRC-TR-90-7, Computer Science Department, University of Maryland, 1989.

[89]  Q. Yang, D. S. Nau, and J. Hendler. An approach to multiple-goal planning with limited interactions. In AAAI Spring Symposium, pp. 64–68, 1989.

[88]  G. Vanecek, Jr. and D. S. Nau. Obtaining boundaries with respect: A simple approach to performing set operations on polyhedra. Tech. Rep. CS-TR-2057, UMIACS-TR-88-48, SRC TR 89-98, University of Maryland, 1989.

[87]  M. Ssemakula, D. S. Nau, R. Rangachar, and Q. Yang. An AI approach to process sequencing. Advances in Manufacturing Engineering 1:271–276, 1989.

[86]  D. S. Nau, Q. Yang, and J. Hendler. Planning for multiple goals with limited interactions. In Fifth IEEE Conference on Artificial Intelligence Applications, 1989.

[85]  D. S. Nau, editor. Proceedings of the First SIGMAN Workshop on Manufacturing Planning. Detroit, Michigan, 1989.

[84]  R. Karinthi and D. S. Nau. Using algebraic properties and boolean operations to compute feature interactions. In AAAI Spring Symposium, 1989.

[83]  D. S. Nau, R. Karinthi, G. Vanecek, Jr., and Q. Yang. Integrating AI and solid modeling for design and process planning. In Second IFIP Working Group 5.2 Workshop on Intelligent CAD. University of Cambridge, Sept. 1988.

[82]  D. S. Nau, N. Ide, R. Karinthi, G. Vanecek, Jr., and Q. Yang. Solid modeling and geometric reasoning for design and process planning. In Third International Conference on CAD/CAM, Robotics, and Factories of the Future, pp. 76–80, Aug. 1988.

[81]  D. Anand, J. Kirk, D. S. Nau, M. Ajanappa, and E. McGrab. Protocol for flexible manufacturing automation with heuristics and intelligence. In Manufacturing International, Apr. 1988.

[80]  P.-C. Chi and D. S. Nau. Improving game board evaluators with genetic algorithms. In 1988 Spring Symposium on Computer Game Playing, Mar. 1988.

[79]  G. Vanecek, Jr. and D. S. Nau. A general method for performing set operations on polyhedra. Tech. Rep. CS TR-1762, SRC TR 87-8, University of Maryland, 1988.

[78]  M. E. Ssemakula, D. S. Nau, R. M. Rangachar, and Q. Yang. Optimal process sequencing in CAPP systems. In AUTOFACT ’88, pp. 22–25–22–27. Society of Manufacturing Engineers, MS88-728, 1988.

[77]  V. Kumar, D. S. Nau, and L. Kanal. A general branch-and-bound formulation for AND/OR graph and game tree search. In L. Kanal and V. Kumar, editors, Search in Artificial Intelligence, pp. 91–130. Springer-Verlag, 1988.

[76]  P.-C. Chi and D. S. Nau. Comparison of the minimax and product back-up rules in a variety of games. In L. N. Kanal and V. Kumar, editors, Search in Artificial Intelligence, pp. 450–471. Springer-Verlag, 1988.

[75]  D. S. Nau and M. Luce. Knowledge representation and reasoning techniques for process planning: Extending SIPS to do tool selection. In 19th CIRP International Seminar on Manufacturing Systems, June 1987.

[74]  G. Vanecek, Jr. and D. S. Nau. Non-regular decomposition: An efficient approach for solving the polygon intersection problem. In C. Liu, A. Requicha, and S. Chandrasekar, editors, Intelligent and Integrated Manufacturing Analysis and Synthesis, volume PED-25, pp. 271–279, 1987. Presented at ASME Winter Annual Meeting.

[73]  G. Vanecek, Jr. and D. S. Nau. Computing geometric boolean operations by input directed decomposition. Tech. Rep. CS TR-1762, SRC TR 87-8, University of Maryland, 1987.

[72]  D. S. Nau and S. Sinha. Integrating feature extraction and process selection. Tech. Rep. 50-483, General Motors Research Labs, 1987.

[71]  D. S. Nau and M. Gray. Hierarchical knowledge clustering: A way to represent and use problem-solving knowledge. In J. Hendler, editor, Expert Systems: The User Interface, pp. 81–98. Ablex, 1987.

[70]  D. S. Nau. SIPS Command Reference Manual. Computer Science Department, University of Maryland, 1987.

[69]  D. S. Nau. Hierarchical abstraction for process planning. In Second International Conference on Applications of Artificial Intelligence in Engineering, 1987. Also available as ISR TR 87-105.

[68]  D. S. Nau. Automated process planning using hierarchical abstraction. TI Technical Journal pp. 39–46, 1987. Award winner, Texas Instruments 1987 Call for Papers on AI for Industrial Automation.

[67]  P.-C. Chi and D. S. Nau. Comparing minimax and product in a variety of games. In National Conference on Artificial Intelligence, pp. 100–104, 1987.

[66]  D. S. Nau and M. Gray. SIPS: An application of hierarchical knowledge clustering to process planning. In C. R. Liu and T. C. Chang, editors, Symposium on Integrated and Intelligent Manufacturing at ASME Winter Annual Meeting, volume PED-Vol. 21, pp. 219–225. ASME, Dec. 1986.

[65]  C. Ramsey, J. A. Reggia, D. S. Nau, and A. Ferrentino. A comparative analysis of methods for expert systems. International Journal of Man-Machine Studies, 1986.

[64]  D. S. Nau and J. A. Reggia. Relationships between abductive and deductive inference in knowledge-based diagnostic problem solving. In L. Kerschberg, editor, Expert Database Systems, pp. 549–558. Benjamin/Cummings Publishing Co., 1986.

[63]  D. S. Nau, P. W. Purdom, Jr., and C. H. Tzeng. Experiments on alternatives to minimax. International Journal of Parallel Programming 15(2):163–183, 1986.

[62]  D. S. Nau, P. W. Purdom, Jr., and C. H. Tzeng. An evaluation of two alternatives to minimax. In L. N. Kanal and J. F. Lemmer, editors, Uncertainty in Artificial Intelligence, pp. 505–509. Elsevier Science Publishers, 1986.

[61]  D. S. Nau and T.-C. Chang. Hierarchical representation of problem-solving knowledge in a frame-based process planning system. International Journal of Intelligent Systems 1(1):29–44, 1986.

[60]  D. S. Nau. Knowledge based expert systems. In J. Zeidner, editor, Human Productivity Enhancement, Vol. 2: Organizations, Personnel, and Decision Making, pp. 236–296. Praeger Publishers, 1986.

[59]  P.-C. Chi and D. S. Nau. Predicting the performance of minimax and product in game tree searching. In Second Workshop on Uncertainty in Artificial Intelligence (UAI), pp. 49–55, 1986.

[58]  D. S. Nau and T. C. Chang. A knowledge-based approach to generative process planning. In C. R. Liu, T. C. Chang, and R. Komanduri, editors, Computer-Aided/Intelligent Process Planning, volume PED-Vol. 19 of ASME Winter Annual Meeting, pp. 65–71, Dec. 1985.

[57]  D. S. Nau and T.-C. Chang. A knowledge-based approach to generative process planning. In Production Engineering Conference at ASME Winter Annual Meeting, pp. 65–71, Nov. 1985.

[56]  D. S. Nau and T.-C. Chang. A control strategy for generative process planning. In Artell ’85: International Symposium and Exposition on Industrial Artificial Intelligence Systems, Research, Applications, and Software Development, Nov. 1985.

[55]  V. Kumar, D. S. Nau, and L. N. Kanal. A generalization of the AO* algorithm. In COMPSAC-85, Oct. 1985.

[54]  D. S. Nau and T.-C. Chang. Forward chaining, hierarchical problem solving, and generative process planning in Prolog. In J. J. Pottmyer, editor, Intelligent Systems: Their Development and Application - 24th Annual Technical Symposium of the Washington, DC Chapter of the ACM, p. 11, June 1985. Extended abstract.

[53]  D. S. Nau. An overview of expert computer systems. In J. H. Cook and J. P. Lamoreux, editors, AIRCON 2: Second International Artificial Intelligence and Robotics Conference, pp. 157–191, June 1985. Invited talk.

[52]   J. A. Reggia, B. Perricone, D. S. Nau, and Y. Peng. Answer justification in abductive expert systems—part II: Supporting plausible justifications. IEEE Transactions on Biomedical Engineering BME-32(4):268–272, 1985.

[51]  J. A. Reggia, B. Perricone, D. S. Nau, and Y. Peng. Answer justification in abductive expert systems—part I: Abductive inference and its justification. IEEE Transactions on Biomedical Engineering BME-32(4):263–267, 1985.

[50]  J. A. Reggia, D. S. Nau, and P. Y. Wang. A formal model of diagnostic inference. II. algorithmic solution and applications. Information Sciences 37:257–285, 1985.

[49]  J. A. Reggia, D. S. Nau, and P. Y. Wang. A formal model of diagnostic inference. I. problem formulation and decomposition. Information Sciences 37:227–256, 1985.

[48]  J. A. Reggia, D. S. Nau, and P. Y. Wang. Diagnostic expert systems based on a set covering model. In J. A. Reggia and S. Tuhrim, editors, Computer-Assisted Medical Decision Making, pp. 159–185. Springer-Verlag, 1985.

[47]  J. A. Reggia, D. S. Nau, Y. Peng, and B. Perricone. A theoretical foundation for abductive expert systems. In M. Gupta, A. Kandel, W. Bandler, and J. Kiszka, editors, Approximate Reasoning in Expert Systems, pp. 459–472. North-Holland, 1985.

[46]  D. S. Nau, P. W. Purdom, Jr., and C. H. Tzeng. An evaluation of two alternatives to minimax. In First Workshop on Uncertainty and Probability in Artificial Intelligence (UAI), pp. 232–236, 1985.

[45]  D. S. Nau and T.-C. Chang. Prospects for process selection using artificial intelligence. In Computer-Aided Process Planning. Society of Manufacturing Engineers, 1985.

[44]  D. S. Nau. SIPP reference manual. Tech. Rep. TR-1515, Computer Science Department, University of Maryland, 1985.

[43]  D. S. Nau. Expert computer systems. Nikkei Computer Special Edition pp. 25–52, 1985.

[42]  V. Kumar, D. S. Nau, and L. N. Kanal. A general paradigm for and/or graph and game tree search. Tech. rep., University of Texas at Austin, 1985.

[41]  J. A. Reggia and D. S. Nau. An abductive non-monotonic logic. In Non-Monotonic Reasoning Workshop, pp. 385–395, Oct. 1984.

[40]  D. S. Nau and J. A. Reggia. Relationships between abductive and deductive inference in knowledge-based diagnostic problem solving. In L. Kerschberg, editor, First International Workshop on Expert Database Systems, pp. 500–509, Oct. 1984.

[39]  D. S. Nau and J. A. Reggia. Knowledge-based problem solving using abductive inference. In Conference on Applied Algorithm Design, July 1984.

[38]  D. S. Nau. Pathological game trees: How to do worse by working harder. In Conference on Applied Algorithm Design, July 1984.

[37]  D. S. Nau, J. A. Reggia, M. W. Blanks, Y. Peng, and D. Sutton. Artificial intelligence approaches for automated process planning and control. Tech. Rep. TR-1382, Computer Science Department, University of Maryland, Feb. 1984.

[36]  J. A. Reggia, D. S. Nau, and P. Y. Wang. Diagnostic expert systems based on a set covering model. In M. J. Coombs, editor, Developments in Expert Systems, pp. 35–58, 1984.

[35]  D. S. Nau, V. Kumar, and L. N. Kanal. General branch and bound, and its relation to A* and AO*. Artificial Intelligence 23(1):29–58, 1984.

[34]  J. A. Reggia, D. S. Nau, and P. Y. Wang. A theory of abductive inference in diagnostic expert systems. Tech. Rep. TR-1338, Computer Science Department, University of Maryland, Dec. 1983.

[33]  D. S. Nau. How to do worse by working harder: The nature of pathology on game trees. In IEEE International Conference on Systems, Man, and Cybernetics (SMC), Dec. 1983.

[32]  J. A. Reggia, D. S. Nau, and P. Y. Wang. A new inference method for frame-based expert systems. In National Conference on Artificial Intelligence, pp. 333–337, Aug. 1983.

[31]  D. S. Nau, J. A. Reggia, and P. Y. Wang. Knowledge-based problem solving without production rules. In IEEE Trends and Applications: Automating Intelligent Behavior, Applications and Frontiers, pp. 105–108, May 1983.

[30]  D. S. Nau. Issues in spatial reasoning and representation for automated process planning. In Workshop on Spatial Knowledge Representation and Processing, May 1983.

[29]  J. A. Reggia, D. S. Nau, and P. Y. Wang. Diagnostic expert systems based on a set covering model. International Journal of Man-Machine Studies pp. 437–460, 1983.

[28]  D. S. Nau and T.-C. Chang. Prospects for process selection using artificial intelligence. Computers in Industry 4:253–263, 1983.

[27]  D. S. Nau. Pathology on game trees revisited, and an alternative to minimaxing. Artificial Intelligence 21(1, 2):221–244, 1983. Reprinted in J. Pearl (ed.), Search and Heuristics, North-Holland Publishing Company, Amsterdam, 1983.

[26]  D. S. Nau. On game graph structure and its influence on pathology. International Journal of Computer and Information Sciences 12(6):367–383, 1983.

[25]  D. S. Nau. Expert computer systems (part II). Nikkei Computer (47):135–184, 1983.

[24]  D. S. Nau. Expert computer systems (part I). Nikkei Computer (46):139–156, 1983.

[23]  D. S. Nau. Expert computer systems. IEEE Computer 16(2):63–85, 1983.

[22]  D. S. Nau. Decision quality as a function of search depth on game trees. Journal of the ACM 30(4):687–708, 1983.

[21]  D. S. Nau. De: An augmented text editor. Tech. Rep. TR-1269, Computer Science Department, University of Maryland, 1983.

[20]  J. A. Reggia, P. Y. Wang, and D. S. Nau. Minimal set covers as a model for diagnostic problem solving. In MEDCOMP ’82 - First IEEE Computer Society International Conference on Medical Computer Sci./Computational Medicine, pp. 340–346, Sept. 1982.

[19]  D. Nau. A brief survey of expert system techniques. In Basili, et al., A Report On DOD’s Software Technology Initiative, pp. 86-104. TR-1161, Dept of Computer Science, University of Maryland, Apr. 1982.

[18]  D. S. Nau. An unusual application of the principle of optimality. Tech. Rep. TR-1154, Computer Science Department, University of Maryland, Mar. 1982.

[17]  D. S. Nau, V. Kumar, and L. N. Kanal. A general paradigm for A.I. search procedures. In National Conference on Artificial Intelligence, 1982.

[16]  D. S. Nau. The last player theorem. Artificial Intelligence 18:53–65, 1982.

[15]  D. S. Nau. An investigation of the causes of pathology in games. Artificial Intelligence 19:257–278, 1982.

[14]  D. S. Nau. Expert computer systems, and their applicability to automated manufacturing. Tech. Rep. NBSIR 81-2466, National Bureau of Standards, 1982.

[13]  D. S. Nau. Expert computer systems: A tutorial. Tech. Rep. TR-1201, Computer Science Department, University of Maryland, 1982.

[12]  D. S. Nau. Pearl’s game is pathological. Tech. Rep. TR-999, Computer Science Department, University of Maryland, Jan. 1981.

[11]  D. S. Nau. Pathology on game trees: A summary of results. In National Conference on Artificial Intelligence, pp. 102–104, 1980.

[10]  D. S. Nau. Preliminary results regarding quality of play versus depth of search in game playing. In First International Symposium on Policy Analysis and Information Systems, pp. 210–217, June 1979.

[9]   D. S. Nau. Quality of Decision Versus Depth of Search on Game Trees. Ph.D. dissertation, Duke University, 1979.

[8]   D. S. Nau, G. Markowsky, M. A. Woodbury, and D. B. Amos. A mathematical analysis of human leukocyte antigen serology. Mathematical Biosciences 40:243–270, 1978.

[7]   D. S. Nau and M. A. Woodbury. A command processor for the determination of specificities from matrices of reactions between blood cells and antisera. Computers and Biomedical Research 10:259–269, 1977.

[6]   D. S. Nau. Specificity Covering: Immunological Applications, Computational Complexity and Other Mathematical Properties, and a Computer Program. Master’s thesis, Duke University, 1976.

[5]   A. W. Biermann and D. S. Nau. Finite-state solutions to the Tower of Hanoi problem. Tech. Rep. CS-1976-18, Computer Science Department, Duke University, 1976.

[4]   D. S. Nau. A note on the correctness of Kugel’s theorem. SIGART Newsletter, 1975.

[3]   D. S. Nau. A theorem proving computer program. In Kappa Mu Epsilon Region 5 Convention, 1974. First place award winner.

[2]   D. S. Nau. A lattice point problem. The Pentagon 31(1):25–28, Fall 1972. First place award winner, Kappa Mu Epsilon Region 5 Convention.

[1]   D. S. Nau. An original proof that ∫ ₁^xdt∕t is the inverse of e^x. In Twenty-First International Science Fair, 1970. Third place award winner.