Accession Number:

AD0613075

Title:

ANALYSIS OF MARKOV CHAIN MODELS OF ADAPTIVE PROCESSES

Descriptive Note:

Technical Report,01 May 1963,31 Mar 1964

Corporate Author:

RCA LABS PRINCETON NJ PRINCETON

Personal Author(s):

Report Date:

1965-01-01

Pagination or Media Count:

117.0

Abstract:

Learning and adaptation are considered to be stochastic in nature by most modern psychologists and by many engineers. Markov chains are among the simplest and best understood models of stochastic processes and, in recent years, have frequently found application as models of adaptive processes. A number of new techniques are developed for the analysis of synchronous and asynchronous Markov chains, with emphasis on the problems encountered in the use of these chains as models of adaptive processes. Signal flow analysis yields simplified computations of asymptotic success probabilities, delay times, and other indices of performance. The techniques are illustrated by several examples of adaptive processes. These examples yield further insight into the relations between adaptation and feedback.

Subject Categories:

Distribution Statement:

APPROVED FOR PUBLIC RELEASE