Measuring heterogeneity between web-based agent communication protocols

Abstract

Communication between multiple agents is essential to achieve goals, cooperation, and negotiation to take decisions for mutual benefit. Nowadays there is a growing interest in automating communication processes between different agents in dynamic Web-based environments. However, when agents are deployed and integrated in open and dynamic environments, detailed syntax and semantics of their particular language implementations differ, causing the problem of communication heterogeneity. Therefore, it is necessary to measure heterogeneity among all participating agents and the number of required translations when heterogeneous agents are involved in communications. In this paper we present a set of measures with the objective to evaluate the minimal computational requirements before implementing a translation approach. Our measures are based on set theory, which has proved to be a good representation formalism in other areas. We showed how to use the set of measures for two highly heterogeneous set of agents.