Probabilistic Network Approach to Decision-Making

Abstract

A probabilistic approach to decision-making is developed in which the states of the underlying stochastic process, assumed to be of the Markov type, represent the competing options. The principal parameters determining the dominance of a particular option versus the others are identified and the transduction of information associated to the transitions between states is quantified using a set of entropy-like quantities.