PROBABILISTIC AWARD STRATEGY FOR CONTRACT NET PROTOCOL IN MASSIVELY MULTI-AGENT SYSTEMS

摘要

We propose a probabilistic award selection strategy for a contract net protocol (CNP) in massively multi-agent systems (MMASs) for effective task allocations. Recent Internet and sensor network applications require sophisticated multi-agent system technologies to enable the large amounts of software and computing resources to be effectively used. Improving the overall performance of MMASs in which thousands of agents work concurrently requires a new negotiation strategy for appropriately allocating tasks to agents. Our proposed method probabilistically selects the awardee in CNP based on the statistical difference between bid values for subtasks that have different costs. We explain how our proposed method can significantly improve the overall performance of MMASs.