84 search results - page 4 / 17 » Exploiting State Constraints in Heuristic State-Space Planni... |
142
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AAAI
1996
15 years 7 months ago
1996
If a state space is not completely known in advance, then search algorithms have to explore it sufficiently to locate a goal state and a path leading to it, performing therefore w...
158
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ICRA
2009
IEEE
16 years 18 days ago
2009
IEEE
— The reduction of the kinematics and/or dynamics of a high-DOF robotic manipulator to a low-dimension “task space” has proven to be an invaluable tool for designing feedback...
198
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IJRR
2011
15 years 27 days ago
2011
Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
183
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LAMAS
2005
Springer
15 years 11 months ago
2005
Springer
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
182
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JAIR
2006
15 years 5 months ago
2006
Fast Downward is a classical planning system based on heuristic search. It can deal with general deterministic planning problems encoded in the propositional fragment of PDDL2.2, ...