Biological Cybernetics

, Volume 40, Issue 3, pp 201–211 | Cite as

Associative search network: A reinforcement learning associative memory

  • Andrew G. Barto
  • Richard S. Sutton
  • Peter S. Brouwer


An associative memory system is presented which does not require a “teacher” to provide the desired associations. For each input key it conducts a search for the output pattern which optimizes an external payoff or reinforcement signal. The associative search network (ASN) combines pattern recognition and function optimization capabilities in a simple and effective way. We define the associative search problem, discuss conditions under which the associative search network is capable of solving it, and present results from computer simulations. The synthesis of sensory-motor control surfaces is discussed as an example of the associative search problem.


Pattern Recognition Computer Simulation Payoff Memory System Function Optimization 
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-Verlag 1981

Authors and Affiliations

  • Andrew G. Barto
    • 1
  • Richard S. Sutton
    • 1
  • Peter S. Brouwer
    • 1
  1. 1.Department of Computer and Information ScienceUniversity of MassachusettsAmherstUSA

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