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COLT
2010
Springer
14 years 10 months ago
Open Loop Optimistic Planning
We consider the problem of planning in a stochastic and discounted environment with a limited numerical budget. More precisely, we investigate strategies exploring the set of poss...
Sébastien Bubeck, Rémi Munos
ML
2002
ACM
143views Machine Learning» more  ML 2002»
14 years 11 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
ICCBR
2007
Springer
15 years 6 months ago
Using Cases Utility for Heuristic Planning Improvement
Current efficient planners employ an informed search guided by a heuristic function that is quite expensive to compute. Thus, ordering nodes in the search tree becomes a key issue,...
Tomás de la Rosa, Angel García Olaya...
ATAL
2006
Springer
15 years 3 months ago
Action awareness: enabling agents to optimize, transform, and coordinate plans
As agent systems are solving more and more complex tasks in increasingly challenging domains, the systems themselves are becoming more complex too, often compromising their adapti...
Freek Stulp, Michael Beetz
EWRL
2008
15 years 1 months ago
Optimistic Planning of Deterministic Systems
If one possesses a model of a controlled deterministic system, then from any state, one may consider the set of all possible reachable states starting from that state and using any...
Jean-François Hren, Rémi Munos