Data Set Used
This is the fifth anniversary of the Robocup Rescue Simulation Competitions and the tenth anniversary of the disaster that inspired the Competitions. This is a good time to take stock of what milestones have been achieved and what milestones we should be aiming for. Specifically , this paper looks at the goals that led to the establishment of the… (More)
The evolving complexity of many modern artifacts, such as aircraft, has led to a serious fragmentation of knowledge among software systems required for their design and manufacture. In the case of aircraft design, views of the same generic design knowledge are redundantly encoded in multiple software systems, each system using its own idiosyncractic… (More)
This paper explores six different representations of the BlocksWorld Domain. It compares the results of seven planners run on these representations. It shows that the rankings for the International Planning Competition, using the non-satisficing scoring function, would change for every representation.
Progress has been made recently in developing techniques to automatically generate effective heuristics. These techniques typically aim to reduce the size of the search tree, usually by combining more primitive heuristics. However, simply reducing search tree size is not enough to guarantee that problems will be solved more quickly. We describe a new… (More)
Humans exhibit the remarkable ability to solve complex, multi-step problems despite their limited capacity for search. We review the standard theory of problem solving, which posits that heuristic guidance makes this possible, but we also note that most studies have emphasized the role of domain-specific heuristics, which are not available for unfamiliar… (More)
This paper describes a system that automatically transforms a PDDL encoding, calls a planner to solve the transformed representation, and translates the solution back into the original representation. The approach involves counting objects that are indistinguishable, rather than treating them as individuals, which eliminates some unnecessary combinatorial… (More)
In this paper we present greedy methods for selecting a subset of heuristic functions for guiding A* search. Our methods are able to optimize various objective functions while selecting a subset from a pool of up to thousands of heuristics. Specifically , our methods minimize approximations of A*'s search tree size, and approximations of A*'s running time.… (More)