The University of Southampton
University of Southampton Institutional Repository

Coevolution of finite automata with errors

Coevolution of finite automata with errors
Coevolution of finite automata with errors
Errors are common in strategic situations. We use a genetic algorithm to simulate the evolution of error-prone finite automata in the repeated Prisoner's Dilemma game. In particular, the automata are subjected to implementation and perception errors. The computational experiments assess whether and how the distribution of outcomes and structures in the population changes with different levels of errors. We find that the complexity of the automata is decreasing in the probability of errors. Furthermore, the prevailing structures tend to exhibit low reciprocal cooperation and low tolerance to defections as the probability of errors increases. In addition, by varying the error-level, the study identifies a threshold error-level. At and above the threshold error-level, the prevailing structures converge to the open-loop (history-independent) automaton Always-Defect. On the other hand, below the threshold, the prevailing structures are closed-loop (history-dependent) and diverse, which impedes any inferential projections on the superiority of a particular machine.
automata, repeated games, prisoner's dilemma, genetic algorithms, local polynomial regression
0966-4246
1019
University of Southampton
Ioannou, Christos A.
753c2afb-918b-4576-ba47-da42502f37c9
Ioannou, Christos A.
753c2afb-918b-4576-ba47-da42502f37c9

Ioannou, Christos A. (2013) Coevolution of finite automata with errors (Discussion Papers in Economics and Econometrics, 1019) Southampton, GB. University of Southampton 41pp.

Record type: Monograph (Discussion Paper)

Abstract

Errors are common in strategic situations. We use a genetic algorithm to simulate the evolution of error-prone finite automata in the repeated Prisoner's Dilemma game. In particular, the automata are subjected to implementation and perception errors. The computational experiments assess whether and how the distribution of outcomes and structures in the population changes with different levels of errors. We find that the complexity of the automata is decreasing in the probability of errors. Furthermore, the prevailing structures tend to exhibit low reciprocal cooperation and low tolerance to defections as the probability of errors increases. In addition, by varying the error-level, the study identifies a threshold error-level. At and above the threshold error-level, the prevailing structures converge to the open-loop (history-independent) automaton Always-Defect. On the other hand, below the threshold, the prevailing structures are closed-loop (history-dependent) and diverse, which impedes any inferential projections on the superiority of a particular machine.

Text
__userfiles.soton.ac.uk_Users_spd_mydesktop_Paper01.pdf - Other
Restricted to Repository staff only
Request a copy

More information

Published date: 17 January 2013
Keywords: automata, repeated games, prisoner's dilemma, genetic algorithms, local polynomial regression
Organisations: Economics

Identifiers

Local EPrints ID: 169599
URI: http://eprints.soton.ac.uk/id/eprint/169599
ISSN: 0966-4246
PURE UUID: 33885f8d-8cbc-4968-b138-098252b9ca82

Catalogue record

Date deposited: 17 Dec 2010 12:51
Last modified: 14 Mar 2024 02:21

Export record

Contributors

Author: Christos A. Ioannou

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×