TY - JOUR
T1 - Negotiation on data allocation in multi-agent environments
AU - Schwartz, Rina
AU - Kraus, Sarit
PY - 1997/12/1
Y1 - 1997/12/1
N2 - We propose a strategic negotiation model that takes into account the passage of time during the negotiation process itself in order to solve the problem of data allocation in environments with self-motivated servers which have no common interest and no central controller. The model considers situations characterized by complete, as well as incomplete, information. Using this negotiation mechanism, the servers have simple and stable negotiation strategies that result in efficient agreements without delays. We provide heuristics for finding the details of the strategies which depend on the specific settings of the environment, and demonstrate the quality of the heuristics, using simulations. We prove that our methods yield better results than the static allocation policy currently used for data allocation for servers in distributed systems.
AB - We propose a strategic negotiation model that takes into account the passage of time during the negotiation process itself in order to solve the problem of data allocation in environments with self-motivated servers which have no common interest and no central controller. The model considers situations characterized by complete, as well as incomplete, information. Using this negotiation mechanism, the servers have simple and stable negotiation strategies that result in efficient agreements without delays. We provide heuristics for finding the details of the strategies which depend on the specific settings of the environment, and demonstrate the quality of the heuristics, using simulations. We prove that our methods yield better results than the static allocation policy currently used for data allocation for servers in distributed systems.
UR - http://www.scopus.com/inward/record.url?scp=31389124&partnerID=8YFLogxK
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JO - Proceedings of the National Conference on Artificial Intelligence
JF - Proceedings of the National Conference on Artificial Intelligence
ER -