Matchmaking among minimal agents without a facilitator

Multi-Agent Systems are a promising way of dealing with large complex problems. However, it is not yet clear just how much complexity or pre-existing structure individual agents must have to allow them to work together effectively. In this paper, we ask to what extent agents with minimal resources, local communication and without a directory service can solve a consumer-provider matchmaking problem. We are interested in finding a solution that is massively scalable and can be used with resource poor agents in an open system. We create a model involving random search and a grouping procedure. Through simulation of this model, we show that peer-to-peer communication in a environment with multiple copies of randomly distributed like clients and providers is sufficient for most agents to discover the service consumers or providers they need to complete tasks. We simulate systems with between 500 and 32,000 agents, between 10 and 2000 categories of services, and with three to six services required by each agent. We show that, for instance, in a system with 80 service categories and 2000 agents, each requiring three random services between 93\% and 97\% of possible matches are discovered. Such a system can work with at least 90 different service categories and tens of thousands of agents.