University of Maryland Department of Computer Science

James A. Reggia's Research Page

Professor, Department of Computer Science, Institute for Advanced Computer Studies
      Neuroscience and Cognitive Science Program
      Maryland Robotics Center
      Applied Mathematics and Scientific Computation Program
University of Maryland, College Park MD

Research Interests:

I am a Professor of Computer Science at the University of Maryland, jointly appointed in the Institute for Advanced Computer Studies. My primary research interests are neural computation, including attractor neural networks, one-step learning, hyper-dimensional computing, programmable neural networks, and neuro-symbolic AI. However, my broader research interests span nature-inspired AI in general, including not only neural computation but also genetic programming, swarm intelligence, cellular automata, artificial life, and machine consciousness. I have also worked in other more traditional areas of AI, such as cause-effect reasoning (abduction), robotic imitation learning, and modeling brain functions that can be related to neurological and neuropsychological disorders (Alzheimer's disease, aphasia, PTSD, etc.). I have authored/co-authored over 250 refereed journal and conference papers in these areas, and I have also taught undergraduate and graduate courses in these fields.

Selected Publications During the Last Ten Years

Monner D, Reggia J. A Generalized LSTM-like Training Algorithm for Second Order Recurrent Neural Networks, Neural Networks, 25, 2012, 70-83.

Chabuk T, Reggia J, Lohn J, Linden D. Causally-Guided Evolutionary Optimization and Its Application to Antenna Array Design, Integrated Computer-Aided Engineering, 19, 2012, 111-124.

Monner D, Reggia J. Neural Architectures for Learning to Answer Questions, Biologically Inspired Cognitive Architectures, 2, 2012, 37-53.

Huynh T, Reggia J. Symbolic Representation of Recurrent Neural Network Dynamics, IEEE Transactions on Neural Networks and Learning Systems, 23, 2012, 1649-1658.

Monner D, Reggia J. Emergent Latent Symbol Systems in Recurrent Neural Networks, Connection Science, 24, 2012, 193-225.

Winder R, Reggia J. The Role of Collective Working Memory in an Urban Pursuit Scenario, in C. Adami, D. Bryson, C. Ofria & R. Pennock (eds.), Proc. 13th International Conference on the Synthesis and Simulation of Living Systems (Alife 13), MIT Press, 2012, 291-298.

Sylvester J, Reggia J, Weems S, Bunting M. Controlling Working Memory with Learned Instructions, Neural Networks, 41, 2013, 23-38.

Reggia J. The Rise of Machine Consciousness: Studying Consciousness with Computational Models, Neural Networks, 44, 2013, 112-131.

Monner D, Reggia J. Recurrent Neural Network Classification, IEEE Transactions on Neural Networks and Learning Systems, 12, 2013, 1932-1943.

Chabuk T, Reggia J. The Added Value of Gating in Evolved Neurocontrollers, Proc. International Joint Conference on Neural Networks, Dallas TX, IEEE, August 2013, 1335-1342.

Grushin A, Monner D, Reggia J, Mishra A. Robust Human Action Recognition via Long Short-Term Memory, Proc. International Joint Conf. on Neural Networks, Dallas TX, IEEE, August 2013, 641-648.

Sylvester J, Reggia J. The Neural Executive: Can Gated Attractor Networks Account for Cognitive Control? Proc. International Association for Computing and Philosophy World Congress, 2013.

Reggia J, Monner D, Sylvester J. The Computational Explanatory Gap, Journal of Consciousness Studies, 21(9), 2014, 153-178.

Gentili R, Oh H, Huang D, Katz G, Miller R, Reggia J. Towards a Multi-Level Neural Architecture that Unifies Self-Intended and Imitated Arm Reaching Performance, Proc. of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 14), August 2014.

Reggia J. Conscious Machines: The AI Perspective, in The Nature of Humans and Machines, Proc. of the AAAI 2014 Fall Symposium Series, Arlington VA, Nov. 2014 (invited), FS-14-07, AAAI Press, 34-37.

Huang D, Gentili R, Reggia J. Limit Cycle Representation of Spatial Locations Using Self-Organizing Maps, Proc. of the IEEE Symposium Series on Computational Intelligence (SSCI), Dec. 2014.

Gentili R, Oh H, Miller R, Huang D, Katz G, Reggia J. A Neural Architecture for Performing Actual and Mentally Simulated Movements, International Journal of Social Robotics, 7 (3), 2015, 371-392.

Seifter, J., Reggia, J. Lambda and the Edge of Chaos in Recurrent Neural Nets, Artificial Life, 21, 2015, 55-71.

Huang D, Gentili R, Reggia J. Self-Organizing Maps Based on Limit Cycle Attractors, Neural Networks, 63, 2015, 208-222.

Reggia J, Huang D, Katz G. Beliefs Concerning the Nature of Consciousness, Journal of Consciousness Studies, 22, 2015, 146-171.

Huang D, Gentili R, Reggia J. A Self-Organizing Map Architecture for Arm Reaching Based on Limit Cycle Attractors, Proc. Ninth Intl. Conference on Bio-Inspired Information and Communication Technology (BICT 2015), New York City, Dec. 2015.

Sylvester J, Reggia J. Engineering Neural Systems for High-Level Problem Solving, Neural Networks, 79, 2016, 37-52.

Katz G, Huang D, Gentili R, Reggia J. Imitation Learning as Cause-Effect Reasoning, Proceedings of the Ninth Annual Conference on Artificial General Intelligence (AGI-16), P. Wang & B. Steunebrink (Eds.), NYC, published as Lecture Notes in Computer Science, Vol. 9782, Springer, July 2016.

Reggia J, Katz G, Huang D. What are the Computational Correlates of Consciousness? Proc. 2016 Annual International Conf. on Biologically Inspired Cognitive Architectures (BICA 2016), NYC, July 2016.

Huang D, Gentili R, Katz G, Reggia J. A Limit Cycle Self-Organizing Map Architecture for Stable Arm Control, Neural Networks, 85, 2017, 165-181.

Reggia J, Huang D, Katz G. Exploring the Computational Explanatory Gap, Philosophies, 2, 5, 2017.

Katz G, Huang D, Gentili R, Reggia J. An Empirical Characterization of Parsimonious Intention Inference for Cognitive-Level Imitation Learning, Proc. 19th Intl. Conf. on Artificial Intelligence (ICAI 17), July 2017.

Katz G, Huang D, Hauge T, Gentili R, Reggia J. A Novel Parsimonious Cause-Effect Reasoning Algorithm for Robot Imitation and Plan Recognition, IEEE Trans. Cognitive and Developmental Systems, 10, 2018, 177-193.

Katz G, Reggia J. Using Directional Fibers to Locate Fixed Points of Recurrent Neural Networks, IEEE Transactions on Neural Networks and Learning Systems, 29. 2018, 3636-3646.

Reggia J, Katz G, Davis G. Humanoid Cognitive Robots that Learn by Imitation, Frontiers in Robotics and AI, Humanoid Robotics Section, 5, Jan. 2018.

Sosis B, Katz G, Reggia J. Learning in a Continuous-Valued Attractor Network, Proceedings of the IEEE International Conference on Machine Learning and Applications, Orlando, December 2018.

Oh H, Braun A, Reggia J, Gentili R. Fronto-Parietal Mirror Neuron System Modeling, Human Movement Science, 65, 2019, 121-141.

Katz G, Davis G, Gentili R, Reggia J. A Programmable Neural Virtual Machine Based on a Fast Store-Erase Learning Rule, Neural Networks, 119, 2019, 10-30.

Krishnagopal S, Katz G, Girvan M, Reggia J. Encoding a Chaotic Attractor in a Reservoir Computer, Proc. International Joint Conference on Neural Networks (IJCNN), Budapest, IEEE, July 2019.

Hauge T, Katz G, Davis G, Jaquess K, Reinhard M, Costanzo M, Reggia J, Gentili R. A Novel Application of Levenshtein Distance for Assessment of High-Level Motor Planning Underlying Performance During Learning of Complex Action Sequences, Journal of Motor Learning and Development, 8, 2020, 67-86.

Reggia J, Katz G, Davis G. Artificial Conscious Intelligence, Journal of Artificial Intelligence and Consciousness, 7, 2020, 1-13.

Hauge T, Katz G, Davis G, Huang D, Reggia J, Gentili R. High-level Motor Planning Assessment During Performance of Complex Action Sequences in Humans and a Humanoid Robot, International Journal of Social Robotics,, August 2020.

Katz G, Gupta K, Reggia J. Reinforcement-Based Program Induction in a Neural Virtual Machine, Proceedings of the International Joint Conference on Neural Networks (IJCNN), Glasgow, United Kingdom, 2020, 1-8.

Davis G, Katz G, Soranzo D, Allen N, Reinhard M, Gentili R Costanzo M, and Reggia J. A Neurocomputational Model of Posttraumatic Stress Disorder, Proceedings of the 10th International IEEE EMBS Conference on Neural Engineering (NERS'21), May 4-6, 2021, 107-110.

Reggia J, Katz G, Davis G, Gentili R. Avoiding Catastrophic Forgetting with Short-Term Memory, Proc. of the 23rd International Conference on Artificial Intelligence (ICAI'21), July 26-29, 2021.

Davis G, Katz G, Gentili R, Reggia J. Compositional Memory in Attractor Neural Networks with One-Step Learning, Neural Networks, 138, 2021, 78-97.

Katz G, Akshay ., Davis G, Gentili R, Reggia J. Tunable Neural Encoding of a Symbolic Robotic Manipulation Algorithm, Frontiers in Neurorobotics, 2021, in press.

Davis G, Katz G, Gentili R, Reggia J. NeuroLISP: High-Level Symbolic Programming with Attractor Neural Networks, Neural Networks, 2021, in press.