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Adele Howe

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5 papers
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5

AIJ Journal 2009 Journal Article

Learning from planner performance

  • Mark Roberts
  • Adele Howe

The planning community has amassed a large body of publicly available problems in a standardized input language and planners that accept the language. We seized this remarkable opportunity to collect data about how some of these planners perform on the benchmark problems. We analyzed the resulting data to learn about the state of the art in Classical planning. Our analyses are retrospective, prescriptive and prospective. The first analyses are retrospective and prescriptive in that they characterize the problems and planners in terms of difficulty, diversity and trends over time. We statistically confirm that problem sets have become more difficult and that new planners are generally more capable. A visualization of planner success on domains shows how the domains distinguish performance. We also assess whether some older planners can be disregarded as out-dated and find that while they are not up to current capabilities, some do provide limited distinct functionality. The second analyses automatically learn models of success and time for each planner. The models are constructed from easily extracted features of problems and domains and use off-the-shelf Machine Learning techniques. We find the models of success to be extremely accurate, but the models of time to be less so. They too are both retrospective and prescriptive in demonstrating the predictability of current planner performance. In a third analysis, we apply the data to an existing explanatory model linking the relationship between the search space and planner performance. Our study validates previous results linking search topology with planner performance on a wider set of planners than the original study. Finally, we fill in some gaps in observed performance of the benchmark problems by constructing new problems; these problems do turn out to be more challenging. This study of existing and new problems and planners is prescriptive and prospective in that the results should help guide researchers in comparatively evaluating their planners and suggest need for additional effort. These analyses highlight the importance of problems in driving research in planning. We show how much can be accomplished with the available resources and point out how much more can be done by broadening the problems available and by learning from what has already been done.

Details DOI

KER Journal 1999 Journal Article

Special issue: Perspectives on intelligent agents research... one year later

  • Simon Parsons
  • Adele Howe

A year ago, we published a special issue of The Knowledge Engineering Review entitled "Perspectives on Recent Intelligent Agents Research as Viewed through Two Conferences". Our intention was to provide a snapshot of current research on intelligent agents - an area which continues to grow apace - by looking at the work presented at the 1997 instantiations of two of the major events in the Agent calendar. These were the International Conference on Autonomous Agents (Agents '97) and the International Conference and Exhibition on the Practical Application of Intelligent Agents and Multi-Agent Technology (PAAM '97). The result was a group of six papers which together spanned the main areas covered by the conferences as well as identifying some of the challenges faced by the agents community as a whole. In particular, we had summaries by the organisers of both of the conferences, speculation on the future of robotics, surveys of expert assistants and electronic commerce, and a discussion of how agents could be used in workflow management.

Details DOI
v2026.09.13