Intrinsically Motivated Machines

نویسندگان

  • Andrew G. Barto
  • Satinder Singh
  • Richard L. Lewis
چکیده

Intrinsic motivation is what causes us to do something “for its own sake,” in contrast to doing something for an external reward. There is great interest in building intrinsic motivation into artificial systems by defining intrinsic reward signals within the reinforcement learning framework. Yet, what intrinsic reward signals are, and how it may differ from extrinsic reward signals, remains a murky and controversial subject. Here we approach this issue from an evolutionary perspective that leads to the conclusion there are no hard and fast features distinguishing intrinsic and extrinsic reward signals. Rather, there is a continuum along which reward signals range that depends on the directness and complexity of the relationship between the rewarded behavior and evolutionary success. This article contains work previously published by the authors and Jonathan Sorg in [26], [27].

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تاریخ انتشار 2011