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SCAI
2008
13 years 9 months ago
Fast Learning in an Actor-Critic Architecture with Reward and Punishment
Abstract. A reinforcement architecture is introduced that consists of three complementary learning systems with different generalization abilities. The ACTOR learns state-action as...
Christian Balkenius, Stefan Winberg
ICTAI
2007
IEEE
14 years 1 months ago
Multi-agent Reinforcement Learning Using Strategies and Voting
Multiagent learning attracts much attention in the past few years as it poses very challenging problems. Reinforcement Learning is an appealing solution to the problems that arise...
Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlah...
ROBOCUP
2009
Springer
134views Robotics» more  ROBOCUP 2009»
14 years 2 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
IJCNN
2006
IEEE
14 years 1 months ago
Learning a Rendezvous Task with Dynamic Joint Action Perception
Abstract— Groups of reinforcement learning agents interacting in a common environment often fail to learn optimal behaviors. Poor performance is particularly common in environmen...
Nancy Fulda, Dan Ventura
FLAIRS
2008
13 years 9 months ago
Learning Continuous Action Models in a Real-Time Strategy Environment
Although several researchers have integrated methods for reinforcement learning (RL) with case-based reasoning (CBR) to model continuous action spaces, existing integrations typic...
Matthew Molineaux, David W. Aha, Philip Moore