Enhancing Agent Intelligence with Behavior Duplication

Wei Tang; Jun Lai

doi:10.4028/www.scientific.net/AMR.403-408.1266

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 403-408Enhancing Agent Intelligence with Behavior...

Enhancing Agent Intelligence with Behavior Duplication

Abstract:

The traditional agent intelligence designing always lead to a fixed behavior manner. In this way, the NPC(Non-Player Character) in the game will act in a fixed and expectable way. It has greatly weakened the long-term attraction of single-played game. Extracting the human action patterns using a statistical-based machine learning algorithm can provide an easily-understanding way to implement the agent behavior intelligence. A daemon program records and sample the human player’s input action and related properties of character and virtual environment, and then apply certain statistical-based machine learning algorithm on the sample data. As a result, a human-similar intelligent behavior model was obtained. It can be used to help agent making an action decision. Repeating the learning process can give the agent a variety of intelligent behavior.

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Periodical:

Advanced Materials Research (Volumes 403-408)

Pages:

1266-1269

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.403-408.1266

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Online since:

November 2011

Authors:

Wei Tang, Jun Lai

Keywords:

Decision Tree, Intelligent Behavior, Statistical-Based Machine Learning

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