The objective of this paper is to examine the crucial area of coordination in multi-agent systems. It does not attempt to provide a comprehensive overview of the coordination literature ; rather, it highlights the necessity for coordination in agent systems and overviews briefly various coordination techniques. It critiques these techniques and presents some conclusions and challenges which we ...

Abstract In artificial multi-agent systems, the ability to learn collaborative policies is predicated upon agents’ communication skills: they must be able encode information received from environment and how share it with other agents as required by task at hand. We present a deep reinforcement learning approach, Connectivity Driven Communication (CDC), that facilitates emergence of behaviour o...

A multi-agent planning problem consists of a set of activities that need to be planned by several agents. Here, plan coordination methods play an important role, since the independently generated plans by different agents can lead to an infeasible joint solution. We study one particular plan coordination approach, called coordination-by-design, which allows each agent to make its own plan compl...

This paper proposes a meta-level control mechanism of coordination protocols in a multi-agent system. In an open environment, an agent needs to respond to unexpected situations (exceptions). By introducing a meta-level control mechanism in the coordination protocol execution, an agent can have flexible control over the coordination with other agents. As a mete-level control mechanism, methods t...

A framework for coordination in multi-agent systems is introduced. The main idea of our framework is that an agent with knowledge about the desired behavior in a certain domain will direct other, domain-independent agents by means of signals which reeect its evaluation of the coordination between its own actions and their actions. Mechanisms for coordination are required to enable construction ...