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AAAI
1997
13 years 7 months ago
Model Minimization in Markov Decision Processes
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Thomas Dean, Robert Givan
ATAL
2009
Springer
14 years 17 days ago
Point-based incremental pruning heuristic for solving finite-horizon DEC-POMDPs
Recent scaling up of decentralized partially observable Markov decision process (DEC-POMDP) solvers towards realistic applications is mainly due to approximate methods. Of this fa...
Jilles Steeve Dibangoye, Abdel-Illah Mouaddib, Bra...
NIPS
2004
13 years 7 months ago
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs
Existing algorithms for discrete partially observable Markov decision processes can at best solve problems of a few thousand states due to two important sources of intractability:...
Pascal Poupart, Craig Boutilier
AMAI
2004
Springer
13 years 11 months ago
Warped Landscapes and Random Acts of SAT Solving
Recent dynamic local search (DLS) algorithms such as SAPS are amongst the state-of-the-art methods for solving the propositional satisfiability problem (SAT). DLS algorithms modi...
Dave A. D. Tompkins, Holger H. Hoos
EC
2006
163views ECommerce» more  EC 2006»
13 years 6 months ago
An Extension of Geiringer's Theorem for a Wide Class of Evolutionary Search Algorithms
The frequency with which various elements of the search space of a given evolutionary algorithm are sampled is affected by the family of recombination (reproduction) operators. Th...
Boris Mitavskiy, Jonathan E. Rowe