&lt;title&gt;Computer-simulation gaming systems utilizing neural networks and genetic algorithms&lt;/title&gt;

Baba, Norio; Kita, Tomio; Takagawara, Y.; Erikawa, Yoichi; Oda, Kazuhiro

doi:10.1117/12.235939

Cited by 6 publications

(2 citation statements)

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“…To decrease burden of players, computer agents using neural-networks and other techniques can play the role of players instead of human beings. In [3], Baba et al showed that a computer agent using the neural-network could join a game as a human player. Furthermore, Morimoto in [4] showed that computer agents who are allowed to make other agents' models explicitly can play a game by using other agent's model inside it.…”

Section: Gaming Simulationmentioning

confidence: 99%

Studies on rule-learning in gaming simulation

Shinoda

Nakamori

2004

37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of The

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Gaming is one of the good tools to deal with complex phenomena. Now, computer agents are beginning to join gaming as substitutes for human players. To help designing of a gaming, this paper proposes a model for gaming-simulation. In this model, each agent has its own neural-networks for predicting behavior of other agents, including itself. In addition, each agent has a classifier model for tactical decisionmaking, and to achieve tactical target, the agent uses neural-networks to get an optimal answer. These agents try to find tactical rules with playing the game that aims at the second phase. It is shown that this three-model structure enables us to monitor behavior of agents easily.

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Section: Gaming Simulationmentioning

confidence: 99%

Studies on rule-learning in gaming simulation

Shinoda

Nakamori

2004

37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of The

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“…The agent has a learning function to find good strategy in a business game. Baba et al [8] show that neural-network system can learn a player's behavior, and the neural-network system can play a game same as the original player. They also show that a genetic algorithm based program can defeat a human player in one-by-one game.…”

Section: Agentsmentioning

confidence: 99%

Design of a software agent for business gaming simulation

Shinoda

Ryoke

Terano

et al. 2006

J. Syst. Sci. Syst. Eng.

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This paper introduces an agent model for one of the business games called Bakery Game. Business game is a tool the understand business and the principle of management through the experience in a virtual world. In order to construct computer agents for the gaming simulation that can participate in the game and become human players' worthy rival, we combine simple model that consider the property of Bakery Game and strategy adjustment model. The agent has so-called strategy parameters that are updated through the experience. The agent changes the strategy depending on the situation. The agent participates in the game that regenerated from log data that recorded various situations.

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Utilization of Neural Networks and Genetic Algorithms to Make Game Playing More Exciting

Baba

Wang

Gaming, Simulations, and Society

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<title>Computer-simulation gaming systems utilizing neural networks and genetic algorithms</title>

Cited by 6 publications

References 0 publications

Studies on rule-learning in gaming simulation

Studies on rule-learning in gaming simulation

Design of a software agent for business gaming simulation

Utilization of Neural Networks and Genetic Algorithms to Make Game Playing More Exciting

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