Srivastava, Biplav


Reports of the AAAI 2014 Conference Workshops

AI Magazine

The AAAI-14 Workshop program was held Sunday and Monday, July 27–28, 2012, at the Québec City Convention Centre in Québec, Canada.


Reports of the AAAI 2012 Conference Workshops

AI Magazine

The AAAI-12 Workshop program was held Sunday and Monday, July 22–23, 2012 at the Sheraton Centre Toronto Hotel in Toronto, Ontario, Canada. The AAAI-12 workshop program included 9 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Activity Context Representation: Techniques and Languages, AI for Data Center Management and Cloud Computing, Cognitive Robotics, Grounding Language for Physical Systems, Human Computation, Intelligent Techniques for Web Personalization and Recommendation, Multiagent Pathfinding, Neural-Symbolic Learning and Reasoning, Problem Solving Using Classical Planners, Semantic Cities. This article presents short summaries of those events.


The Workshops at the Twentieth National Conference on Artificial Intelligence

AI Magazine

The AAAI-05 workshops were held on Saturday and Sunday, July 9-10, in Pittsburgh, Pennsylvania. The thirteen workshops were Contexts and Ontologies: Theory, Practice and Applications, Educational Data Mining, Exploring Planning and Scheduling for Web Services, Grid and Autonomic Computing, Human Comprehensible Machine Learning, Inference for Textual Question Answering, Integrating Planning into Scheduling, Learning in Computer Vision, Link Analysis, Mobile Robot Workshop, Modular Construction of Humanlike Intelligence, Multiagent Learning, Question Answering in Restricted Domains, and Spoken Language Understanding.


AltAlt: Combining Graphplan and Heuristic State Search

AI Magazine

AltAlt is designed to exploit the complementary strengths of two of the currently popular competing approaches for plan generation: (1) graphplan and (2) heuristic state search. It uses the planning graph to derive effective heuristics that are then used to guide heuristic state search. The heuristics derived from the planning graph do a better job of taking the subgoal interactions into account and, as such, are significantly more effective than existing heuristics. AltAlt was implemented on top of two state-of-the-art planning systems: (1) stan3.0, a graphplan-style planner, and (2) hsp-r, a heuristic search planner.