A framework for facilitating cooperation in multi-agent systems

Abstract

This work introduces a multi-agent framework that facilitates cooperation in multi-agent robotic systems. It uses a layered approach based on Coloured Petri Nets for modelling complex, concurrent conversations among agents. In this approach each agent employs a Coloured Petri Net model that allows agents to follow a plan specifying their interactions. It also allows programmers to plan for the concurrent feature of the conversation and make sure that all possible states of the problem space are considered. The framework assists the agents to identify and adapt different strategies for teammates and task selection dynamically. The agents can change their strategies in the course of dynamic environments to improve their performance. We have examined the performance of the agents in this framework by developing some task selection and teammate selection strategies for agents in a disaster scenario.