Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Quantum Conditional Strategies for Prisoners' Dilemmata Under the Ewl Scheme

Konstantinos Giannakis
* ORCID logo ,
Georgia Theocharopoulou
,
Christos Papalitsas
ORCID logo ,
Sofia Fanarioti
,
Theodore Andronikos
*
Version 1 : Received: 29 May 2019 / Approved: 30 May 2019 / Online: 30 May 2019 (10:20:31 CEST)

A peer-reviewed article of this Preprint also exists.

Giannakis, K.; Theocharopoulou, G.; Papalitsas, C.; Fanarioti, S.; Andronikos, T. Quantum Conditional Strategies and Automata for Prisoners’ Dilemmata under the EWL Scheme. Appl. Sci. 2019, 9, 2635. Giannakis, K.; Theocharopoulou, G.; Papalitsas, C.; Fanarioti, S.; Andronikos, T. Quantum Conditional Strategies and Automata for Prisoners’ Dilemmata under the EWL Scheme. Appl. Sci. 2019, 9, 2635.

Abstract

Classic game theory is an important field with a long tradition of useful results. Recently, the quantum versions of classical games, such as the Prisoner's Dilemma (PD), have attracted a lot of attention. Similarly, state machines and specifically finite automata have also been under constant and thorough study for plenty of reasons. The quantum analogues of these abstract machines, like the quantum finite automata, have been studied extensively. In this work, we examine some well-known game conditional strategies that have been studied within the framework of the repeated PD game. Then, we try to associate these strategies to proper quantum finite automata that receive them as inputs and recognize them with probability 1, achieving some interesting results. We also study the quantum version of PD under the Eisert-Wilkens-Lewenstein scheme, proposing a novel conditional strategy for the repeated version of this game.

Keywords

quantum game theory; quantum automata; prisoner's dilemma; conditional strategies; quantum strategies

Subject

Computer Science and Mathematics, Computer Science

Copyright: 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.

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