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IJCAI
2003

A Bayesian Approach to Imitation in Reinforcement Learning

10 years 1 days 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 learning (RL). We recast the problem of imitation in a Bayesian framework. Our Bayesian imitation model allows a learner to smoothly pool prior knowledge, data obtained through interaction with the environment, and information inferred from observations of expert agent behaviors. Our model integrates well with recent Bayesian exploration techniques, and can be readily generalized to new settings.
Bob Price, Craig Boutilier
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where IJCAI
Authors Bob Price, Craig Boutilier
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