Risk-Sensitive Probability for Markov Chains

Abstract

The probability distribution of a Markov chain is viewed as the information state of an additive optimization problem. This optimization problem is then generalized to a product form whose information state gives rise to a generalized notion of probability distributionfor Markov chains. The evolution and the asymptoticbehavior of this generalized or "risk-sensitive"probability distribution is studied in this paper and a conjecture isproposed regarding the asymptotic periodicity of risk-sensitive probability. The relation between a set of simultaneous non-linear equations and the set of periodic attractors is analyzed.