RELATIONAL SEQUENCE BASED CLASSIFICATION IN MULTI-AGENT SYSTEMS

Grazia Bombini, Nicola Di Mauro, Stefano Ferilli, Floriana Esposito

2010

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.

Paper Citation

in Harvard Style

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, pages 619-622. DOI: 10.5220/0002731306190622

in Bibtex Style

@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},
}

in EndNote Style

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
AU - Bombini G.
AU - Di Mauro N.
AU - Ferilli S.
AU - Esposito F.
PY - 2010
SP - 619
EP - 622
DO - 10.5220/0002731306190622