ASSOCIATIVE SEARCH NETWORK - A REINFORCEMENT LEARNING ASSOCIATIVE MEMORY

Abstract

Abstract. 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. Numerous reports have appeared in the literature describing associative memory systems in which information is distributed across large areas of the physical memory structure (e.g., Amari, 1977; Anderson et al.,