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» Implicit Imitation in Multiagent Reinforcement Learning
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ICML
1999
IEEE
10 years 4 months ago
Implicit Imitation in Multiagent Reinforcement Learning
Imitation is actively being studied as an effective means of learning in multi-agent environments. It allows an agent to learn how to act well (perhaps optimally) by passively obs...
Bob Price, Craig Boutilier
CORR
2011
Springer
194views Education» more  CORR 2011»
8 years 7 months ago
Accelerating Reinforcement Learning through Implicit Imitation
Imitation can be viewed as a means of enhancing learning in multiagent environments. It augments an agent’s ability to learn useful behaviors by making intelligent use of the kn...
Craig Boutilier, Bob Price
IJCAI
2003
9 years 5 months ago
A Bayesian Approach to Imitation in Reinforcement Learning
In multiagent environments, forms of social learning such as teaching and imitation have been shown to aid the transfer of knowledge from experts to learners in reinforcement lear...
Bob Price, Craig Boutilier
AI
2001
Springer
9 years 8 months ago
Imitation and Reinforcement Learning in Agents with Heterogeneous Actions
Reinforcement learning techniques are increasingly being used to solve di cult problems in control and combinatorial optimization with promising results. Implicit imitation can acc...
Bob Price, Craig Boutilier
ECAI
2008
Springer
9 years 5 months ago
Exploiting locality of interactions using a policy-gradient approach in multiagent learning
In this paper, we propose a policy gradient reinforcement learning algorithm to address transition-independent Dec-POMDPs. This approach aims at implicitly exploiting the locality...
Francisco S. Melo
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