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Discovering Effective Strategies for the Iterated Prisoner?s Dilemma using Genetic Algorithms
Wroclaw, Poland September 08-September 10
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISDA.2005.385th International Conference on Intel ...
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Michal Glomba, Tomasz Filak, Halina Kwasnicka, "Discovering Effective Strategies for the Iterated Prisoner?s Dilemma using Genetic Algorithms," Intelligent Systems Design and Applications, International Conference on, pp. 356-363, 5th International Conference on Intelligent Systems Design and Applications (ISDA'05), 2005.
 
 
BibTex
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@article{ 10.1109/ISDA.2005.38,
author = {Michal Glomba and Tomasz Filak and Halina Kwasnicka},
title = {Discovering Effective Strategies for the Iterated Prisoner?s Dilemma using Genetic Algorithms},
journal ={Intelligent Systems Design and Applications, International Conference on},
volume = {0},
year = {2005},
isbn = {0-7695-2286-6},
pages = {356-363},
doi = {http://doi.ieeecomputersociety.org/10.1109/ISDA.2005.38},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Intelligent Systems Design and Applications, International Conference on
TI - Discovering Effective Strategies for the Iterated Prisoner?s Dilemma using Genetic Algorithms
SN - 0-7695-2286-6
SP356
EP363
A1 - Michal Glomba,
A1 - Tomasz Filak,
A1 - Halina Kwasnicka,
PY - 2005
KW - null
VL - 0
JA - Intelligent Systems Design and Applications, International Conference on
ER -
 
Michal Glomba, Wroclaw University of Technology, Poland
Tomasz Filak, Wroclaw University of Technology, Poland
Halina Kwasnicka, Wroclaw University of Technology, Poland
The iterated prisoner?s dilemma is used to illustrate and model the phenomena in economics, sociology, psychology, as well as in the biological sciences such as evolutionary biology. The discovery and optimization of IPD strategies in real-world applications requires flexible strategy representation. The comparison of deterministic and non-deterministic finite state machines as the representations of strategies for the iterated prisoner?s dilemma is presented. A novel chromosome representation scheme for nondeterministic Mealy finite state machines is proposed. The research on efficiency of the strategies evolved using genetic algorithms was made. Best results in competition with unknown strategies were obtained by non-deterministic strategies.
Citation:
Michal Glomba, Tomasz Filak, Halina Kwasnicka, "Discovering Effective Strategies for the Iterated Prisoner?s Dilemma using Genetic Algorithms," isda, pp.356-363, 5th International Conference on Intelligent Systems Design and Applications (ISDA'05), 2005
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