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Authors: Grazia Bombini 1 ; Nicola Di Mauro 2 ; Stefano Ferilli 2 and Floriana Esposito 2

Affiliations: 1 Università degli Studi di Bari, Italy ; 2 Università degli Studi di Bari; Università degli Studi di Bari, Italy

Keyword(s): Group behavior, Adversary classification, Sequence learning, Relational sequence similarity.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Computational Intelligence ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Machine Learning ; Multi-Agent Systems ; Soft Computing ; Software Engineering ; Symbolic Systems

Abstract: In multiagent adversarial environments, the adversary consists of a team of opponents that may interfere with the achievement of goals. In this domain agents must be able to quickly adapt to the environment and infer knowledge from other agents' deportment to identify the future behaviors of opponents. We present a relational model to characterize adversary teams based on its behavior. A team's deportment is represent by a set of relational sequences of basic actions extracted from their observed behaviors. Based on this, we present a similarity measure to classify the teams' behavior. The sequence extraction and classification are implemented in the domain of simulated robotic soccer, and experimental results are presented.

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Paper citation in several formats:
Bombini, G.; Di Mauro, N.; Ferilli, S. and Esposito, F. (2010). RELATIONAL SEQUENCE BASED CLASSIFICATION IN MULTI-AGENT SYSTEMS. In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-674-021-4; ISSN 2184-433X, SciTePress, pages 619-622. DOI: 10.5220/0002731306190622

@conference{icaart10,
author={Grazia Bombini. and Nicola {Di Mauro}. and Stefano Ferilli. and Floriana Esposito.},
title={RELATIONAL SEQUENCE BASED CLASSIFICATION IN MULTI-AGENT SYSTEMS},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2010},
pages={619-622},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002731306190622},
isbn={978-989-674-021-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - RELATIONAL SEQUENCE BASED CLASSIFICATION IN MULTI-AGENT SYSTEMS
SN - 978-989-674-021-4
IS - 2184-433X
AU - Bombini, G.
AU - Di Mauro, N.
AU - Ferilli, S.
AU - Esposito, F.
PY - 2010
SP - 619
EP - 622
DO - 10.5220/0002731306190622
PB - SciTePress

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