Probabilistic Roadmaps (PRM) are a commonly used class of algorithms for robot navigation tasks where obstacles are present in the environment. We examine the situation where the ...
Temporally expressive planning, an important class of temporal planning, has attracted much attention lately. Temporally expressive planning is difficult; few existing planners ca...
In order to scale with modern processors, planning algorithms must become multi-threaded. In this paper, we present parallel shared-memory algorithms for two problems that underli...
While several powerful domain-independent planners have recently been developed, no one of these clearly outperforms all the others in every known benchmark domain. We present PbP...
Alfonso Gerevini, Alessandro Saetti, Mauro Vallati
Current state-of-the-art planners solve problems, easy and hard alike, by search, expanding hundreds or thousands of nodes. Yet, given the ability of people to solve easy problems...
This paper considers Just-In-Time Job-Shop Scheduling, in which each activity has an earliness and a tardiness cost with respect to a due date. It proposes a constraint programmin...
N-gram analysis provides a means of probabilistically predicting the next item in a sequence. Due originally to Shannon, it has proven an effective technique for word prediction i...
Christian J. Muise, Sheila A. McIlraith, Jorge A. ...
abstraction heuristics, notably pattern-database and merge-and-shrink heuristics, are employed by some state-ofthe-art optimal heuristic-search planners. The major limitation of t...