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  • Martin V. Butz
Part of the Genetic Algorithms and Evolutionary Computation book series (GENA, volume 4)

Abstract

The last chapters introduced and evaluated the ACS2 learning mechanism. The intensive investigation showed that ACS2 is able to tackle a large variety of problems ranging from hard classification problems to big environmental tasks. The genetic generalization mechanism confirmed to be capable to further generalize the evolving environmental model working together with the directed specialization caused by an anticipatory learning process (ALP). Several distinct challenges revealed the actual shortcomings in the system. Model exploitation processes were able to overcome several of the challenges as well as were able to further increase model learning performance and adaptivity. Model exploitation also showed the distinct adaptive behavior capabilites of the system. All in all, the last chapters provided a unified few of the functioning, capabilities, and limits of the current ACS2 system.

Keywords

Reinforcement Learning Learning Mechanism Goal Directed Behavior Behavioral Module Reinforcement Learning Algorithm 
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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