The background chapter illustrated an important cognitive aspect of the current knowledge about learning. The insight of the presence and importance of anticipations in animals and man leads to the conclusion that it is mandatory to represent and learn anticipations also in animats. Furthermore, once this task is accomplished, it is necessary to investigate how the usefulness of anticipations can be exploited by the animat. The development of such a system and the exploitation of the anticipations in the resulting system is the enterprise of the remainder of this book.


Genetic Algorithm Reinforcement Learning Effect Part Environmental Niche Genetic Algorithm Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Martin V. Butz
    • 1
  1. 1.University of WürzburgGermany

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