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» Admissible Heuristics for Optimal Planning
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AIPS
2008
13 years 11 months ago
Learning Heuristic Functions through Approximate Linear Programming
Planning problems are often formulated as heuristic search. The choice of the heuristic function plays a significant role in the performance of planning systems, but a good heuris...
Marek Petrik, Shlomo Zilberstein
SARA
2000
Springer
14 years 4 days ago
Recent Progress in the Design and Analysis of Admissible Heuristic Functions
In the past several years, significant progress has been made in finding optimal solutions to combinatorial problems. In particular, random instances of both Rubik's Cube, wi...
Richard E. Korf
AAAI
2004
13 years 10 months ago
Distance Estimates for Planning in the Discrete Belief Space
We present a general framework for studying heuristics for planning in the belief space. Earlier work has focused on giving implementations of heuristics that work well on benchma...
Jussi Rintanen
AI
2008
Springer
13 years 8 months ago
Sequential Monte Carlo in reachability heuristics for probabilistic planning
The current best conformant probabilistic planners encode the problem as a bounded length CSP or SAT problem. While these approaches can find optimal solutions for given plan leng...
Daniel Bryce, Subbarao Kambhampati, David E. Smith
AIPS
2006
13 years 10 months ago
Sequential Monte Carlo in Probabilistic Planning Reachability Heuristics
The current best conformant probabilistic planners encode the problem as a bounded length CSP or SAT problem. While these approaches can find optimal solutions for given plan leng...
Daniel Bryce, Subbarao Kambhampati, David E. Smith