Discovering pragmatic similarity relations between agent interaction protocols

Abstract

A multi-agent system (MAS) consists of a set of autonomous agents, capable of interacting among each other with cooperation or coordination purposes. To achieve their goals, all agents in a MAS must exchange messages following a interaction protocol. Currently there are research efforts to provide standard mechanisms to achieve cooperation between multiple heterogeneous MAS. However, there are still some issues that must be solved in order to fully automate integration and inter-operation among them. In this paper we present a novel approach for discovering pragmatic similarity among multiple agent interaction protocols, our objective is to support system developers and integrators generating a set of pragmatic relations between pairs of agent interaction protocols and a numerical measure which represents the similarity among them. We describe an example to show the applicability of our approach.