Learning to Achieve Goals

@inproceedings{Kaelbling1993LearningTA,
  title={Learning to Achieve Goals},
  author={Leslie Pack Kaelbling},
  booktitle={IJCAI},
  year={1993}
}
Temporal diierence methods solve the temporal credit assignment problem for reinforcement learning. An important subproblem of general reinforcement learning is learning to achieve dynamic goals. Although existing temporal diierence methods, such as Q learning, can be applied to this problem, they do not take advantage of its special structure. This paper presents the DG-learning algorithm, which learns eeciently to achieve dynamically changing goals and exhibits good knowledge transfer between… CONTINUE READING

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