Table of Contents
Journal of Complex Systems
Volume 2013, Article ID 390454, 6 pages
Research Article

Bluffing as a Rational Strategy in a Simple Poker-Like Game Model

1Department of Education and Psychology, University of Florence, Via San Salvi 12, Building 26, 50135 Florence, Italy
2Statistical Materials Modeling Laboratory (CNR-IENI), Via R. Cozzi 53, 20125 Milano, Italy

Received 28 January 2013; Accepted 8 May 2013

Academic Editor: Fuwen Yang

Copyright © 2013 Andrea Guazzini and Daniele Vilone. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We present a simple adaptive learning model of a poker-like game, by means of which we show how a bluffing strategy emerges very naturally and can also be rational and evolutionarily stable. Despite their very simple learning algorithms, agents learn to bluff, and the most bluffing player is usually the winner.