Authors: Michail Zak
A QRN simulating human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which represent the motor dynamics, and of classical neural nets describing evolution of probabilities of these processes which represent the mental dynamics. The autonomy of the decision making process is achieved by a feedback from mental to motor dynamics which changes the stochastic matrix based upon the probability distributions. This feedback replaces an unavailable external information by an internal knowledgebase stored in the mental model in the form of probability distributions. As a result, the coupled motor-mental dynamics is described by a nonlinear version of Markov chains which can decrease entropy without an external source of information. Applications to common sense based decisions as well as to evolutionary games are discussed.
Comments: 24 Pages.
[v1] 2016-02-18 19:28:27
Unique-IP document downloads: 39 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.