Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science

Complex Information Game Problem Based on Artificial Neural Network

Authors
Xingfeng Liu, Tiansong Zhou, Zhongxia Zheng
Corresponding Author
Xingfeng Liu
Available Online July 2015.
DOI
https://doi.org/10.2991/lemcs-15.2015.34How to use a DOI?
Keywords
Artificial intelligence; Artificial neural network; Complex information; Game theory
Abstract
The assumption of game theory is that the players in game must be rational. In the game of incomplete information, participants are not completely clear about the game. Therefore, usually there is a probability distribution of strategy selection in game. It is very complicated to know the real game information of the social and economic problems. In fact, the actual situation for many problems is that game players are irrational, or the probability distribution of game players’ strategies cannot be gotten, even the strategy sets are not complete (infinite strategy sets).There are many limitations in application of the traditional game theory. In this paper, the concept of complex information game and its Nash equilibrium are presented. It is proved that the complex information game problem can be solved by artificial neural network. An example on how to solve the complex information game problem with artificial neural network is given as well. Researchers hope that more and more scholars can use artificial intelligence theory to analyze the game theory problem. Therefore, the complex information game problems can be dealt more efficiently.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
International Conference on Logistics Engineering, Management and Computer Science (LEMCS 2015)
Part of series
Advances in Intelligent Systems Research
Publication Date
July 2015
ISBN
978-94-6252-102-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/lemcs-15.2015.34How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Xingfeng Liu
AU  - Tiansong Zhou
AU  - Zhongxia Zheng
PY  - 2015/07
DA  - 2015/07
TI  - Complex Information Game Problem Based on Artificial Neural Network
BT  - International Conference on Logistics Engineering, Management and Computer Science (LEMCS 2015)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-15.2015.34
DO  - https://doi.org/10.2991/lemcs-15.2015.34
ID  - Liu2015/07
ER  -