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CPAIOR
2010
Springer
14 years 21 days ago
Strong Combination of Ant Colony Optimization with Constraint Programming Optimization
We introduce an approach which combines ACO (Ant Colony Optimization) and IBM ILOG CP Optimizer for solving COPs (Combinatorial Optimization Problems). The problem is modeled using...
Madjid Khichane, Patrick Albert, Christine Solnon
UAI
1997
13 years 9 months ago
A Scheme for Approximating Probabilistic Inference
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
Rina Dechter, Irina Rish
ICML
2005
IEEE
14 years 8 months ago
Bayesian sparse sampling for on-line reward optimization
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
ISMIS
2005
Springer
14 years 1 months ago
A Probabilistic Approach to Finding Geometric Objects in Spatial Datasets of the Milky Way
Data from the Sloan Digital Sky Survey has given evidence of structures within the Milky Way halo from other nearby galaxies. Both the halo and these structures are approximated by...
Jon Purnell, Malik Magdon-Ismail, Heidi Jo Newberg
ECAI
2004
Springer
14 years 1 months ago
On-Line Search for Solving Markov Decision Processes via Heuristic Sampling
In the past, Markov Decision Processes (MDPs) have become a standard for solving problems of sequential decision under uncertainty. The usual request in this framework is the compu...
Laurent Péret, Frédérick Garc...