Data-Driven Behavior-Based Negotiation Model for Cyber-Physical-Social Systems

This paper presents an agent-based fuzzy constraint-directed negotiation (AFCN) model for cyber-physical-social systems (CPSS). The proposed AFCN model is a behavior-based negotiation framework, which involves the agents perceive the opponents' behavior and market environment to evaluate the proposal and revise the intention to guide the behavior of agent which represent the goal the agents aim to achieve. The novelty of the proposed model is to add the fuzzy membership function to exchange information between the cyber, physical, and social worlds for representing the imprecise Quality of Service (QoS) preferences that must be satisfied. This added information sharing is of critical importance for the effectiveness of distributed coordination because it not only reveals the opponent's behavior preference but also can specify the possibilities prescribing the extent to which the feasible solutions are suitable for agent's behavior. Moreover, the AFCN model can flexibly adopt different behavioral strategies such as the competitive, win-win, collaborative, and hybrid strategies for classic market environments which enable an agent to reach an agreement benefit all participants without reducing any of an agent's desires. The experimental results demonstrate that the proposed behavior-based agent negotiation model outperforms other agent-based approaches in terms of the level of satisfaction, the ratio of successful negotiation, the total revenue of service providers, the buying price of the unit resource, and convergence speed.