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Algorithms for Reinforcement Learning

  • Category: Computer
  • Author: Csaba Szepesvari
  • Pages: : 104 pages
  • File type: : PDF

Read and download free eBook intituled Algorithms for Reinforcement Learning in format : PDF – : 104 pages created by Csaba Szepesvari.

Reinforcement Learning (RL) is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective.What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner’s predictions.

Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms’ merits and limitations.

Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering.

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Algorithms for Reinforcement Learning

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