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Decision Making Model Based on State Assessment and Hierarchical FSM in Robot Soccer

Yunfeng Lou, Haobin Shi, Bin Chen

Year
2012
Citations
7

Abstract

In order to improve validity and pertinence of strategies in robot soccer, this paper put forward a finite state automatons hierarchical decision model based on match state estimations. This model synthesizes and quantitates the information of state estimations and feedback of performing effects, establishes tactics conversion relationship based on finite state automatons, accordingly makes a tactic suiting current states. The simulations indicate that the decision model in this paper improves validity and pertinence of tactics to a great extent, enabling that whole abilities of attacking and defending for the soccer team attain corresponding melioration.

Keywords

Computer scienceState (computer science)RobotArtificial intelligenceFinite-state machineOrder (exchange)Finite stateMachine learningAlgorithm

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