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ICMLA
2004
13 years 11 months ago
A new discrete binary particle swarm optimization based on learning automata
: The particle swarm is one of the most powerful methods for solving global optimization problems. This method is an adaptive algorithm based on social-psychological metaphor. A po...
Reza Rastegar, Mohammad Reza Meybodi, Kambiz Badie
AAAI
1996
13 years 11 months ago
Formalizing Dependency Directed Backtracking and Explanation Based Learning in Refinement Search
The ideas of dependency directed backtracking (DDB) and explanation based learning (EBL) have developed independently in constraint satisfaction, planning and problem solving comm...
Subbarao Kambhampati
AAMAS
2005
Springer
14 years 3 months ago
Advice-Exchange Between Evolutionary Algorithms and Reinforcement Learning Agents: Experiments in the Pursuit Domain
This research aims at studying the effects of exchanging information during the learning process in Multiagent Systems. The concept of advice-exchange, introduced in (Nunes and Ol...
Luís Nunes, Eugénio C. Oliveira
CDC
2009
IEEE
107views Control Systems» more  CDC 2009»
14 years 2 months ago
Learning approaches to the Witsenhausen counterexample from a view of potential games
— Since Witsenhausen put forward his remarkable counterexample in 1968, there have been many attempts to develop efficient methods for solving this non-convex functional optimiz...
Na Li, Jason R. Marden, Jeff S. Shamma
AAAI
2007
14 years 13 days ago
Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison
Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
Matthew E. Taylor, Shimon Whiteson, Peter Stone