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FPGA implementation of a network of neuronlike adaptive elements

  • Andrés Pérez-Uribe
  • Eduardo Sanchez
Part VIII: Implementations
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1327)

Abstract

A well known model of reinforcement learning is called Adaptive Heuristic Critic learning. It is composed of two so called “neuronlike adaptive elements” and has been used to solve difficult learning control problems. In this paper we present an FPGA design and implementation of such algorithm, and, furthermore, we describe a neurocontroller system composed of a network of neuronlike adaptive elements and an unsupervised clustering system called FAST, which dynamically partitions the input state space of the system being controlled.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Andrés Pérez-Uribe
    • 1
  • Eduardo Sanchez
    • 1
  1. 1.Logic Systems Laboratory, Computer Science DepartmentSwiss Federal Institute of Technology-LausanneLausanneSwitzerland

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