Multi-Agent Negotiation in B2C E-Commerce Based on Data Mining Methods

The Multi agent system (MAS) model has been extensively used in the different tasks of e-commerce like customer relation management (CRM), negotiation and brokering. For the success of CRM, it is important to target the most profitable customers of a company. This paper presents a multi-attribute negotiation approach for negotiation between buyer and seller agents. The communication model and the algorithms for various actions involved in the negotiation process is described. The paper also proposes a multi-attribute based utility model, based on price, response-time, and quality. In support of this approach, a prototype system providing negotiation between buyer agents and seller agents is presented.

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Multi-Agent Negotiation Paradigm for Agent Selection in B2C E-Commerce

Theoretical and Practical Frameworks for Agent-Based Systems ◽

10.4018/978-1-4666-1565-6.ch011 ◽

2012 ◽

pp. 164-186

Author(s):

Bireshwar Dass Mazumdar ◽

Swati Basak ◽

Neelam Modanwal

Keyword(s):

Cognitive Model ◽

Multi Agent System ◽

Agent System ◽

Negotiation Model ◽

Negotiation Strategies ◽

Agent Negotiation ◽

Customer Relation Management ◽

Agent Selection ◽

Multi Agent

Multi agent system (MAS) model has been extensively used in the different tasks of E-Commerce such as customer relation management (CRM), negotiation and brokering. The objective of this paper is to evaluate a seller agent’s various cognitive parameters like capability, trust, and desire. After selecting a best seller agent from ordering queue, it applies negotiation strategies to find the most profitable proposal for both buyer and seller. This mechanism belongs to a semi cooperative negotiation type, and selecting a seller and buyer agent pair using mental and cognitive parameters. This work provides a logical cognitive model, logical negotiation model between buyer agent and selected seller agent.

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Multi-Agent Negotiation Paradigm for Agent Selection in B2C E-Commerce

International Journal of Agent Technologies and Systems ◽

10.4018/jats.2011040103 ◽

2011 ◽

Vol 3 (2) ◽

pp. 33-52 ◽

Cited By ~ 1

Author(s):

Bireshwar Dass Mazumdar ◽

Swati Basak ◽

Neelam Modanwal

Keyword(s):

Cognitive Model ◽

Multi Agent System ◽

Agent System ◽

Negotiation Model ◽

Negotiation Strategies ◽

Agent Negotiation ◽

Customer Relation Management ◽

Agent Selection ◽

Multi Agent

Multi agent system (MAS) model has been extensively used in the different tasks of E-Commerce such as customer relation management (CRM), negotiation and brokering. The objective of this paper is to evaluate a seller agent’s various cognitive parameters like capability, trust, and desire. After selecting a best seller agent from ordering queue, it applies negotiation strategies to find the most profitable proposal for both buyer and seller. This mechanism belongs to a semi cooperative negotiation type, and selecting a seller and buyer agent pair using mental and cognitive parameters. This work provides a logical cognitive model, logical negotiation model between buyer agent and selected seller agent.

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A rendezvous based coordination and communication model for multi-agent system

IEEE Conference Anthology ◽

10.1109/anthology.2013.6784731 ◽

2013 ◽

Author(s):

Pooya Deldar Gohardani ◽

Roohollah Mirsharifi ◽

Mohammad Reza Meybodi

Keyword(s):

Communication Model ◽

Multi Agent System ◽

Agent System ◽

Multi Agent

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Negotiation Process for Resource Allocation in Grid Using a Multi-agent System

Mobility Aware Technologies and Applications - Lecture Notes in Computer Science ◽

10.1007/978-3-540-30178-3_15 ◽

2004 ◽

pp. 158-167 ◽

Cited By ~ 2

Author(s):

Lilian Noronha Nassif ◽

Mohamed Ahmed ◽

José Marcos Nogueira ◽

Roger Impey

Keyword(s):

Resource Allocation ◽

Negotiation Process ◽

Multi Agent System ◽

Agent System ◽

Multi Agent

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Study on Networked Technical Service System Oriented Production Process

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.315-316.651 ◽

2006 ◽

Vol 315-316 ◽

pp. 651-655 ◽

Cited By ~ 7

Author(s):

Tian Biao Yu ◽

Ya Dong Gong ◽

Jie Liu ◽

G. Yu ◽

Wan Shan Wang

Keyword(s):

Production Process ◽

High Efficiency ◽

Service System ◽

Prototype System ◽

Technical Service ◽

Multi Agent System ◽

Service Information ◽

Key Technologies ◽

Multi Agent ◽

And Function

To improve the quality and efficiency of technical service, shorten the producing cycle of product, a new mode of technical service is presented, which is networked technical service based on the multi-Agent technique, network technique and modern communications technique. The architecture and function of the networked technical service system oriented production-NTSS are researched, and the key technologies including multi-Agent system, virtual assembling oriented the process of production and the assignment and rank of technical service information are studied. The workflow of NTSS is discussed, and base on these theories a prototype system is established, and the security, practicability and high efficiency of NTSS are proved.

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Formal modelling and verification of a multi-agent negotiation approach for airline operations control

Journal of Reliable Intelligent Environments ◽

10.1007/s40860-020-00123-0 ◽

2021 ◽

Author(s):

Soufiane Bouarfa ◽

Reyhan Aydoğan ◽

Alexei Sharpanskykh

Keyword(s):

Disruption Management ◽

System Modelling ◽

Multi Agent System ◽

Airline Operations ◽

Agent System ◽

Formal Modelling ◽

Agent Negotiation ◽

New Strategy ◽

Operations Control ◽

Multi Agent

AbstractThis paper proposes and evaluates a new airline disruption management strategy using multi-agent system modelling, simulation, and verification. This new strategy is based on a multi-agent negotiation protocol and is compared with three airline strategies based on established industry practices. The application concerns Airline Operations Control whose core functionality is disruption management. To evaluate the new strategy, a rule-based multi-agent system model of the AOC and crew processes has been developed. This model is used to assess the effects of multi-agent negotiation on airline performance in the context of a challenging disruption scenario. For the specific scenario considered, the multi-agent negotiation strategy outperforms the established strategies when the agents involved in the negotiation are experts. Another important contribution is that the paper presents a logic-based ontology used for formal modelling and analysis of AOC workflows.

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A Multi-Agent System for Improving the Resource Allocation on Programmes in Higher Education

Intelligent Technologies and Techniques for Pervasive Computing - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-4666-4038-2.ch005 ◽

2013 ◽

pp. 85-107

Author(s):

Constanta-Nicoleta Bodea ◽

Radu-Ioan Mogos

Keyword(s):

Higher Education ◽

Negotiation Process ◽

Resources Allocation ◽

Multi Agent System ◽

University Management ◽

Agent System ◽

Initial Stage ◽

Multi Agent ◽

The University ◽

Academic Resources

The chapter presents UNIRA, a multi-agent system developed by the authors for a Romanian university in order to improve the resources allocation for educational programmes and courses. Different types of resources are required to deliver programmes and courses. Considering a set of resources inquires, issued by programmes and courses, UNIRA system performs a transparent negotiation process between the managers of these resources, to find the solution for the allocation problem. During the initial stage of the multi-agent system deployment, only two types of resources are considered, professors and teaching rooms. The system is now in the validation phase. After the complete validation, the system will be integrated into the university management system. The UNIRA experience is relevant not exclusively for the academic resources management, but also for a large variety of domains, including the load distribution, production planning, computer scheduling, portfolio selection, and apportionment.

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Research and Application of Mobile Agent in E-Commerce System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.519-520.458 ◽

2014 ◽

Vol 519-520 ◽

pp. 458-461 ◽

Cited By ~ 1

Author(s):

Lei Che ◽

Xiao Ping Yang

Keyword(s):

Mobile Agent ◽

Agent Technology ◽

Prototype System ◽

Object Model ◽

Multi Agent System ◽

Combine Result ◽

Key Technologies ◽

Process Collaboration ◽

Multi Agent ◽

The Common

Mobile Agent (MA) is the combine result of Agent technology and distributed technology. MA can move according to the hope of user; MA can take action independently according to the change of environment; MA can return the result after finishing the task. On the basis of analysis of the problems of traditional e-commerce, the design thought of E-Commerce based on MA is proposed. Combining the characteristics, object model, message mechanism and the common software package of IBM Aglet platform, the design framework of E-Commerce based on MA is put forward, the design aims, architecture, and concrete process, collaboration message between Multi-Agent, system safety program are confirmed. At last, the validity of the study is proved by the prototype system, and the key technologies in the implementation are discussed.

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Customer Orientation Based Multi-Agent Negotiation for B2C e-Commerce

International Journal of Agent Technologies and Systems ◽

10.4018/jats.2010040103 ◽

2010 ◽

Vol 2 (2) ◽

pp. 24-48 ◽

Cited By ~ 1

Author(s):

Bireshwar Dass Mazumdar ◽

R. B. Mishra

Keyword(s):

Organizational Culture ◽

Computational Model ◽

Customer Orientation ◽

Multi Agent System ◽

Agent System ◽

Agent Negotiation ◽

Crucial Component ◽

Multi Agent ◽

Selection Of

The Multi Agent System (MAS) model has been extensively used in different e-commerce tasks. Customer orientation is a crucial component of organizational culture and attention to information about customers’ needs should be considered a firm’s most basic value. In this paper, the authors evaluate a seller agent’s various cognitive parameters, such as capability, trust, and desire. The authors also examine customer orientation value for a pair of buyer and seller agents, such as selecting a seller and buyer agent pair using mental and cognitive parameters, customer orientation value for their mutual benefits, and the competitive negotiation factor. The authors provide a deterministic customer orientation computational model, a competitive negotiation computational model between buyer agent and seller agent, and a logical computational model for selection of the best buyer-seller agent pair. With the help of GUI intermediate, final results are shown.

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