Simulation Based Design for Adaptive Multi-Agent Systems with the ADELFE Methodology

Abstract

Complex systems are qualified by the heterogeneity of the involved actors, the large mass of data, the distribution of the manipulated information and the dynamic of the environment in which they are immersed. Designing such systems necessitate theory and methodology. This paper is situated in the AMAS theory and the ADELFE methodology. The AMAS theory (Adaptive Multi-Agent System) was proposed to model complex systems. The ADELFE methodology was proposed to guide the AMAS designer. Building AMAS systems is not an easy task. The objective of the authors' work is to make the task of the AMAS designer less difficult. This paper details two main contributions that the authors proposed in this field. The first contribution consists in improving the ADELFE methodology by simulation techniques. The second contribution consists in enhancing the AMAS agent behavior by giving it the ability to self-design.

S-DLCAM: A Self-Design and Learning Cooperative Agent Model for Adaptive Multi-agent Systems

“…Indeed, we consider that the Self-Design and Learning Cooperative Agent (S-DLCA) life cycle goes through two levels: the preliminary level (PL) (nominal and cooperative behaviour) given by the designer and the heigh level (HL) which is responsible of the detection and correction of the Non Cooperative Situations (NCS) that the agent may encounter during its life. This model was developed under SeSAm (http://www.simsesam.de/) and it can be used by any AMAS designer in order to help him in the detection and correction of the NCS using the new ADELFE methodology extensions [6].…”