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» Skill Combination for Reinforcement Learning
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IJCAI
2001
15 years 6 months ago
Reinforcement Learning in Distributed Domains: Beyond Team Games
Using a distributed algorithm rather than a centralized one can be extremely beneficial in large search problems. In addition, the incorporation of machine learning techniques lik...
David Wolpert, Joseph Sill, Kagan Tumer
CPAIOR
2010
Springer
15 years 10 months 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
ROBOCUP
2009
Springer
134views Robotics» more  ROBOCUP 2009»
15 years 11 months ago
Learning Complementary Multiagent Behaviors: A Case Study
As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
Shivaram Kalyanakrishnan, Peter Stone
AUTOMATICA
2008
198views more  AUTOMATICA 2008»
15 years 3 months ago
Asynchronous cellular learning automata
Cellular learning automata is a combination of cellular automata and learning automata. The synchronous version of cellular learning automata in which all learning automata in dif...
Hamid Beigy, Mohammad Reza Meybodi
ICML
2003
IEEE
16 years 6 months ago
Relativized Options: Choosing the Right Transformation
Relativized options combine model minimization methods and a hierarchical reinforcement learning framework to derive compact reduced representations of a related family of tasks. ...
Balaraman Ravindran, Andrew G. Barto