A quantum device simulating human decision making process is introduced. It
consists of quantum recurrent nets generating stochastic processes which r
epresent the motor dynamics, and of classical neural nets describing evolut
ion of probabilities of these processes which represent the mental dynamics
. The autonomy of the decision making process is achieved by a feedback fro
m mental to motor dynamics which changes the stochastic matrix based upon t
he probability distributions. This feedback replaces an unavailable externa
l information by an internal knowledgebase stored in the mental model in th
e form of probability distributions. As a result, the coupled motormental d
ynamics is described by a nonlinear version of Markov chains which can decr
ease entropy without an external source of information. Applications to com
mon sense based decisions as well as to evolutionary games are discussed. (
C) 2000 Elsevier Science Inc. All rights reserved.