Browsing by Author "Lotem, Amnon"
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Item Facilitating Network Data Exploration with Query Previews: A Study of User Performance and Preference(1998-10-15) Tanin, Egemen; Lotem, Amnon; Haddadin, Ihab; Shneiderman, Ben; Plaisant, Catherine; Slaughter, LauraCurrent 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)Item Facilitating Network Data Exploration with Query Previews: A Study of User Performance and Preference(1998) Tanin, E.; Lotem, Amnon; Haddadin, Ihab; Shneiderman, B.; Plaisant, C.; Slaughter, L.; ISRCurrent 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 by 1.6 to 2.1 times and led to higher subjective satisfaction.Item On the Use of Integer Programming Models in AI Planning(1999) Vossen, Thomas; Ball, Michael O.; Lotem, Amnon; Nau, Dana; ISRRecent research has shown the promise of using propositional reasoning and search to solve AI planning problems. In this paper, we further explore this area by applying Integer Programming to solve AI planning problems. The application of Integer Programming to AI planning has a potentially significant advantage, as it allows quite naturally for the incorporation of numerical constraints and objectives into the planning domain. Moreover, the application of Integer Programming to AI planning addresses one of the challenges in propositional reasoning posed by Kautz and Selman, who conjectured that the principal technique used to solve Integer Programs---the linear programming (LP) relaxation---is not useful when applied to propositional search. We discuss various IP formulations for the class of planning problems based on the STRIPS paradigm. Our main objective is to show that a carefully chosen IP formulation significantly improves the "strength" of the LP relaxation, and that the resultant LPs are useful in solving the IP and the associated planning problems. Our results clearly show the importance of choosing the "right" representation, and more generally the promise of using Integer Programming techniques in the AI planning domain.Item SHOP and M-SHOP: Planning with Ordered Task Decomposition(2000-06-17) Nau, Dana; Cao, Yue; Lotem, Amnon; Munoz-Avila, HectorSHOP (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.Item SHOP: Simple Hierarchical Ordered Planner(1999-03-17) Nau, Dana; Cao, Yue; Lotem, Amnon; Munoz-Avia, HectorSHOP (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)