Collaborative environments, where multiple heterogeneous agents (managing several resources) can cooperate in pursuing common and individual goals, are a step forward in creating real-world agent societies. However, current research in agent negotiation and in service coordination is still not enough for building such an agent-based society, capable of jointly solving complex planning problems and still achieve overall good performance. Most often, current work relies on either some centralised component or pre-defined social structure, which can compromise the system in terms of scalability, openness and robustness, and fails to address general problems. By using efficient network search algorithms and network evolution techniques it is possible to build and maintain a semantic overlay network from a totally unstructured distributed network, which in turn will simplify and optimize the distributed planning process amongst heterogeneous agents. We developed distributed versions of well-known planners that operate on top of the referred semantic overlay network and through a set of tests (using different scenarios) we were able to determine which is the best algorithm.

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Multi-agent coordination,Planning algorithms,Graphplan,Peer-to-peer networks,Semantic overlay networks

• Computer and Information Sciences - Natural Sciences
• Other Engineering and Technology Sciences - Engineering and Technology
• Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology

This publication is an output of the following project(s):

• Task Decomposition And Delegation Algorithms For Coordinating Agent Cooperation In Unstructured Open Agent Societies