Hector Geffner

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In the AIPS98 Planning Contest, the HSP planner showed that heuristic search planners can be competitive with state-of-the-art Graphplan and SAT planners. Heuristic search planners like HSP transform planning problems into problems of heuristic search by automatically extracting heuristics from Strips encodings. They differ from specialized problem solvers(More)
RTDP is a recent heuristic-search DP algorithm for solving non-deterministic planning problems with full observability. In relation to other dynamic programming methods, RTDP has two benefits: first, it does not have to evaluate the entire state space in order to deliver an optimal policy, and second, it can often deliver good policies pretty fast. On the(More)
The [ornntlation of planning as heuristk: search with heuristics derived from problem representations ]nas turned out to be a fruitful approach for cla..,...ical planning. In this paper, we, pur.,,ue a sinnilar idea in Ihe context pLa.nning with incomplete inh)rmation. Planning with incomphit.e iTnforntalion can be formulatvd as a pmbh’nt of search in(More)
In the recent AIPS98 Planning Competition, the hsp planner , based on a forward state search and a suitable domain-independent heuristic, showed that heuristic search planners can be competitive with state of the art Graphplan and Satissability planners. hsp solved more problems than the other planners but often took more time or produced longer plans. The(More)
tlSP ~tm[ HSPr iLrt~ two r(’¢’Pllt p].allllors th~tt st.,trch th," statt~-Sl);.’," 1tsiltg i).lt heuristic fl|n,’tiolt (’xtt’act,’,l froill Strips cnt’tMiatgs, liSP dot’s a f(,rward s(mrch frtmt the ialt.bd stlttt, rt:vc,tuputiltg tim Imuristic in vv(.ry static. whih: HSPr tit)its a l’t:grt.ssit,u s(.~Lr0’h fl’cJm th(. g0,:tl t’,,utpuling ~t .-uitalth.(More)
Recent algorithms like RTDP and LAO* combine the strength of Heuristic Search (HS) and Dynamic Programming (DP) methods by exploiting knowledge of the initial state and an admissible heuristic function for producing optimal policies without evaluating the entire space. In this paper, we introduce and analyze three new HS/DP algorithms. A first general(More)
The ability to plan and react in dynamic environments is central to intelligent behavior yet few algorithms have managed to combine fast planping with a robust execution. In this paper we develop one such algorithm by looking at planning as real time search. For that we develop a variation of Korf’s Learning Real Time A* algorithm together with a suitable(More)
Now welcome, the most inspiring book today from a very professional writer in the world, default reasoning casual and conditional theories. This is the book that many people in the world waiting for to publish. After the announced of this book, the book lovers are really curious to see how this book is actually. Are you one of them? That's very proper. You(More)
entered the second planning contest held at the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS’00). HSP2.0 is a domain-independent planning algorithm that implements the family of heuristic search planners that are characterized by the state space that is searched (either progression or regression space), the search(More)