Matchmaking is the process of introducing two or more agents to each other. Current matchmaking techniques are unidirectional and fail to address large-scale and highly dynamic systems with time constraints. We propose a new distributed technique which scales well, and still maintains relatively low matchmaking time and communication overhead. Our technique introduces very low storage and computational overhead to the agents. We suggest using a matching cache which can take advantage of the multidirectional nature of the matchmaking problem. We empirically evaluate the proposed technique on bilateral matchmaking and show that it outperforms the existing techniques. Categories and Subject Descriptors I.2.1 [Distributed Artificial Intelligence]: Multiagent systems General Terms Algorithms, Performance, Experimentation Keywords Matchmaking; Peer to Peer; Distributed; Evaluation
Victor Shafran, Gal A. Kaminka, Sarit Kraus, Claud