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SHOP and M-SHOP: Planning with Ordered Task Decomposition. Dana Nau. Yue Cao. Amnon Lotem. Hector Munoz-Avila. June 2000.
SHOP (Simple Hierarchical Ordered Planner) and M-SHOP (Multi-task-list SHOP) are planning algorithms with the following characteristics. * SHOP and M-SHOP plan for tasks in the same order that they will later be executed. This avoids some task-interaction issues that arise in other HTN planners, making the planning algorithms relatively simple. This also makes it easy to prove soundness and completeness results. * Since SHOP and M-SHOP know the complete world-state at each step of the planning process, they can use highly expressive domain representations. For example, they can do planning problems that require Horn-clause inferencing, complex numeric computations, and calls to external programs. * In our tests, SHOP and M-SHOP were several orders of magnitude faster than Blackbox, IPP, and UMCP, and were several times as fast as TLplan. * The approach is powerful enough to be used in complex real-world planning problems. For example, we are using a Java implementation of SHOP as part of the HICAP plan-authoring system for Noncombatant Evacuation Operations (NEOs). In this paper, we describe SHOP and M-SHOP, present soundness and completeness results for them, and compare them experimentally to Blackbox, IPP, TLplan, and UMCP. The results suggest that planners that generate totally ordered plans starting from the initial state can "scale up" to complex planning problems better than planners that use partially ordered plans. Department of Computer Science, University of Maryland,
SHOP: Simple Hierarchical Ordered Planner. Dana Nau. Yue Cao. Amnon Lotem. Hector Munoz-Avia. January 1999.
SHOP (Simple Hierarchical Ordered Planner) is a domain-independent HTN Planning system with the following characteristics. * SHOP plans for tasks in the same order that they will later be executed. This avoids some of the goal-interaction issues that arise in other HTN planners, thus making the planning algorithm relatively simple. * The planning algorithm is sound and complete over a large class of problems. * Since SHOP knows the complete world-state at each step of the planning process, it can use highly expressive domain representations. For example, it can do planning problems that require complex numeric computations. * In our tests, SHOP solved problems several orders of magnitude faster than Blackbox and TLplan. This occured even though SHOP is written in Lisp and the other planners are written in C. (Also cross-referenced as UMIACS-TR 99-04) University of Maryland Institute for Advanced Computer Studies, Department of Computer Science, University of Maryland,
Facilitating Network Data Exploration with Query Previews: A Study of. Egemen Tanin. Amnon Lotem. Ihab Haddadin. Ben Shneiderman. Catherine Plaisant. Laura Slaughter. February 1998.
Current network data exploration systems which use command languages (e.g. SQL) or form fill-in interfaces fail to give users an indication of the distribution of data items. This leads many users to waste time posing queries which have zero-hit or mega-hit result sets. Query previewing is a novel visual approach for browsing huge networked information warehouses. Query previews supply data distribution information about the database that is being searched and give continuous feedback about the size of the result set for the query as it is being formed. Our within-subjects empirical comparison studied 12 subjects using a form fill-in interface with and without query previews. We found statistically significant differences showing that query previews sped up performance 1.6 to 2.1 times and led to higher subjective satisfaction. (Also cross-referenced as UMIACS-98-14) University of Maryland Institute for Advanced Computer Studies, Department of Computer Science, University of Maryland,
Last Generated Fri Aug 11 04:01:01 EDT 2000