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Automated Behavior Modeling — Recognizing and Predicting Agent Behavior

  • Jan Wendler
Chapter
  • 537 Downloads
Part of the CISM International Centre for Mechanical Sciences book series (CISM, volume 482)

Abstract

This work addresses a way of automatically classifying and an attempt at predicting the behavior of a team of agents, based on external observation only.

Case Based Reasoning is a feasible approach for recognizing and predicting behavior of agents within the RoboCup domain. Using the method described here, on average 98.4 percent of all situations within a game of virtual robotic soccer have been successfully classified as part of a behavior pattern. Based on the assumption that similar triggering situations lead to similar behavior patterns, a prediction accuracy of up to 0.54 was possible, compared to 0.17 corresponding to random guessing. Significant differences are visible between different teams, which is dependent on the strategic approaches of these teams.

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Copyright information

© CISM, Udine 2006

Authors and Affiliations

  • Jan Wendler
    • 1
  1. 1.BerlinGermany

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