Smart spaces are open complex computing systems, consisting of a large variety of cooperative smart things. Central to building smart spaces is the support for sophisticated coordination among diverse smart things collaborating to accomplish specified tasks. Multi-agent systems are often used as the software infrastructures to address the coordination in smart spaces. However, since agents in s...

Multi-agent planning involves finding a plan for each agent in a group where the goals, the actions and the initial resources are distributed over these autonomous agents. An algorithm is given for multi-agent planning that constructs coordinated agent plans distributedly. Instead of designing a planning algorithm and a coordination method separately, this algorithm integrates planning and coor...

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 ...

The existing multi-agent reinforcement learning methods (MARL) for determining the coordination between agents focus on either global-level or neighborhood-level agents. However problem of individual is remain to be solved. It crucial an optimal coordinated policy in unknown environments analyze agent's roles and correlation To this end, paper we propose agent-level based MARL method. Specifica...