Next Article in Journal
Network Formation with Endogenous Link Strength and Decreasing Returns to Investment
Next Article in Special Issue
Cognitive Hierarchy Theory and Two-Person Games
Previous Article in Journal
Probabilistic Unawareness
Previous Article in Special Issue
Coevolution of Cooperation and Layer Selection Strategy in Multiplex Networks
Open AccessArticle

Modeling Poker Challenges by Evolutionary Game Theory

Department of Mathematics and Computer Science, University of Cagliari, Cagliari 09124, Italy
Academic Editors: Attila Szolnoki and Ulrich Berger
Games 2016, 7(4), 39;
Received: 17 November 2016 / Revised: 28 November 2016 / Accepted: 1 December 2016 / Published: 7 December 2016
(This article belongs to the Special Issue Evolutionary Games and Statistical Physics of Social Networks)
We introduce a model for studying the evolutionary dynamics of Poker. Notably, despite its wide diffusion and the raised scientific interest around it, Poker still represents an open challenge. Recent attempts for uncovering its real nature, based on statistical physics, showed that Poker in some conditions can be considered as a skill game. In addition, preliminary investigations reported a neat difference between tournaments and ‘cash game’ challenges, i.e., between the two main configurations for playing Poker. Notably, these previous models analyzed populations composed of rational and irrational agents, identifying in the former those that play Poker by using a mathematical strategy, while in the latter those playing randomly. Remarkably, tournaments require very few rational agents to make Poker a skill game, while ‘cash game’ may require several rational agents for not being classified as gambling. In addition, when the agent interactions are based on the ‘cash game’ configuration, the population shows an interesting bistable behavior that deserves further attention. In the proposed model, we aim to study the evolutionary dynamics of Poker by using the framework of Evolutionary Game Theory, in order to get further insights on its nature, and for better clarifying those points that remained open in the previous works (as the mentioned bistable behavior). In particular, we analyze the dynamics of an agent population composed of rational and irrational agents, that modify their behavior driven by two possible mechanisms: self-evaluation of the gained payoff, and social imitation. Results allow to identify a relation between the mechanisms for updating the agents’ behavior and the final equilibrium of the population. Moreover, the proposed model provides further details on the bistable behavior observed in the ‘cash game’ configuration. View Full-Text
Keywords: poker; evolutionary game theory; population dynamics; PACS; 89.20.-a poker; evolutionary game theory; population dynamics; PACS; 89.20.-a
Show Figures

Figure 1

MDPI and ACS Style

Javarone, M.A. Modeling Poker Challenges by Evolutionary Game Theory. Games 2016, 7, 39.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

Games, EISSN 2073-4336, Published by MDPI AG
Back to TopTop