Coordinating patient preferences through automated negotiation: A multiagent systems model for diagnostic services scheduling

We assume a decentralized environment in which patients are modeled as self-interested agents who behave strategically to advance their own benefits rather than the system wide performance. The objective is to improve the utilization of diagnostic imaging resources by coordinating patient individual preferences through automated negotiation.

The negotiation process consists of two stages, namely patient selection and preference scheduling. The contractnet protocol and simulated annealing based meta-heuristics are used to design negotiation protocols at the two stages respectively. In terms of game theoretic properties, we show that the proposed protocols are individually rational and incentive compatible.