L. Torrey, J. Shavlik, S. Natarajan, P. Kuppili & T. Walker (2008).
Transfer in Reinforcement Learning via Markov Logic Networks. AAAI'08 Workshop on Transfer Learning for Complex Tasks, Chicago, IL.
Slides (PPT).

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Abstract:

We propose the use of statistical relational learning, and in particular the formalism of Markov Logic Networks, for transfer in reinforcement learning. Our goal is to extract relational knowledge from a source task and use it to speed up learning in a related target task. We do so by learning a Markov Logic Network that describes the source-task Q-function, and then using it for decision making in the early learning stages of the target task. Through experiments in the RoboCup simulated-soccer domain, we show that this approach can provide a substantial performance benefit in the target task.

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