Behavior-analysis and -prediction for agents in real-time and dynamic adversarial environments

Carsten Rachuy, Ubbo Visser

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We present an approach for recognition and subsequent prediction of spatio-temporal patterns in a physical real-time environment. The motivation is to provide a domain-independent approach for the analysis of agent's behavior in adversarial multi-agent scenarios. The goal is to create an opponent- specific model, which is used for behavior prediction. We develop a framework for representing a set of hierarchically structured facts, events and actions using temporal logic. Recognition, learning, and prediction is performed using a probabilistic approach utilizing Bayesian Networks. The system is applied to the domain of the RoboCup 3D Simulation League and evaluated with regard to the recognition-, prediction- and realtime capabilities.

Original languageEnglish (US)
Title of host publicationECAI 2010
PublisherIOS Press
Pages979-980
Number of pages2
ISBN (Print)9781607506058
DOIs
StatePublished - Jan 1 2010
Event2nd Workshop on Knowledge Representation for Health Care, KR4HC 2010, held in conjunction with the 19th European Conference in Artificial Intelligence, ECAI 2010 - Lisbon, Portugal
Duration: Aug 17 2010Aug 17 2010

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume215
ISSN (Print)0922-6389

Conference

Conference2nd Workshop on Knowledge Representation for Health Care, KR4HC 2010, held in conjunction with the 19th European Conference in Artificial Intelligence, ECAI 2010
Country/TerritoryPortugal
CityLisbon
Period8/17/108/17/10

ASJC Scopus subject areas

  • Artificial Intelligence

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