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Lecture Notes in Computer Science
We describe a reinforcement learning system that transfers skills from a previously learned source task to a related target task. The system uses inductive logic programming to analyze experience in the source task, and transfers rules for when to take actions. The target task learner accepts these rules through an advice-taking algorithm, which allows learners to benefit from outside guidance that may be imperfect. Our system accepts a human-provided mapping, which specifies the similaritiesdoi:10.1007/11871842_41 fatcat:pf3hi2hs6jhb5ghag2epn756xq