Learning opponent’s beliefs via fuzzy constraint-directed approach to make effective agent negotiation

Lai, K. Robert; Lin, Menq Wen; Yu, Tong

doi:10.1007/s10489-009-0162-2

Cited by 18 publications

(8 citation statements)

References 23 publications

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“…Meanwhile, the CA-to-PA and hPA-to-fPA negotiations can be regarded as different tier of DFCN. [46,47], where…”

Section: Intercloud Negotiation Modelmentioning

confidence: 99%

“…However, if the agent achieves an additional solution from the second-tier, the agent must be integrated into the first-tier negotiation solution, and the maximum appropriateness solution * S of the first-tier is proposed by ranking the feasible integrated solutions of the two tiers, as follows. A is the marginal particularized possibility distribution in the space k X and is defined by [46] as follows.…”

Section: Step 3: Feasible Solution Generationmentioning

confidence: 99%

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Agent-based Multi-tier SLA Negotiation for Intercloud

Lin

Zhu

2021

Preprint

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The evolving intercloud enables idle resources to be traded among cloud providers to facilitate optimizing utilization and to improve the cost-effectiveness of service for cloud consumers. However, several challenges are raised for this multi-tier dynamic market, where cloud providers not only compete for consumer requests but also cooperate with each other. To establish a healthier and more efficient intercloud ecosystem, this paper proposed a multi-tier agent-based fuzzy constraint-directed negotiation (AFCN) model for a fully distributed negotiation environment without a broker to coordinate the negotiation process. The novelty of AFCN is the use of a fuzzy membership function to represent imprecise preferences of the agent, which not only reveals the opponent’s behavior preference but can also specify the possibilities prescribing the extent to which the feasible solutions are suitable for the agent’s behavior. Moreover, this information can pass and guide each tier of negotiation to generate a more favorable proposal. Thus, the multi-tier AFCN can not only improve the performance of negotiation, but also enforce global consistency to improve the integrated solution capacity in the intercloud. The experimental results demonstrate that the proposed multi-tier AFCN model outperforms other agent negotiation models and gives full play to the efficiency and scalability of the intercloud in terms of the level of satisfaction, the ratio of successful negotiation, the average revenue of the cloud provider, and the buying price of the unit cloud resource.

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“…Meanwhile, the CA-to-PA and hPA-to-fPA negotiations can be regarded as different tier of DFCN. [46,47], where…”

Section: Intercloud Negotiation Modelmentioning

confidence: 99%

Section: Step 3: Feasible Solution Generationmentioning

confidence: 99%

Agent-based Multi-tier SLA Negotiation for Intercloud

Lin

Zhu

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…, A * N X ) over the set of objects X k about the issues and N X is the total number of objects. Each element A * q is the marginal particularized possibility distribution in the space X k of the k th agent and is defined by [29], as follows:…”

Section: Negotiation Behavior Of Afcnmentioning

confidence: 99%

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

Lai

Zhu

2019

IEEE Access

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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.INDEX TERMS Cyber-physical-social, multi-agent system, negotiation, behavior model, fuzzy constraints.

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“…Other learning techniques exist, such as volume-base measurement learning (Vetschera, 2009), ontology-based learning (Aydogan and Yolum, 2009), and fuzzy constraint-directed approach (Lai et al, 2009). They were not considered in this study because they have been used in only one context so far and therefore their general applicability and ability in dealing with different negotiation circumstances have not been demonstrated yet.…”

Section: Artificial Neural Networkmentioning

confidence: 99%