scholarly journals A Negotiation Optimization Strategy of Collaborative Procurement with Supply Chain Based on Multi-Agent System

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Chouyong Chen ◽  
Chao Xu
Keyword(s):  
Machine Learning ◽  
Adaptive Learning ◽  
Learning Effect ◽  
Multi Agent System ◽  
Optimization Strategy ◽  
Agent System ◽  
Negotiation Model ◽  
Multi Agent ◽  
Learning Machine ◽  
Self Adaptive

In the process of collaborative procurement, buyers and suppliers are prone to conflict in cooperation due to differences in needs and preferences. Negotiation is a crucial way to resolve the conflict. Aimed at ameliorating the situations of underdeveloped self-adaptive learning effect of current collaborative procurement negotiation, this paper constructs a negotiation model based on multi-agent system and proposes a negotiation optimization strategy combined with machine learning. It provides a novel perspective for the analysis of intelligent SCM. The experimental results suggest that the proposed strategy improves the success rate of self-adaptive learning and joint utility of agents compared with the strategy of single learning machine, and it achieves win-win cooperation between purchasing enterprise and supplier.

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

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.

Adaptive E-Learning Environments

2013 ◽  
Vol 11 (3) ◽  
pp. 1-11 ◽  
Author(s):  
Pierpaolo Di Bitonto ◽  
Teresa Roselli ◽  
Veronica Rossano ◽  
Maria Sinatra
Keyword(s):  
Distance Learning ◽  
Learning Environments ◽  
Recommender System ◽  
Adaptive Learning ◽  
Multi Agent System ◽  
Agent System ◽  
Educational Environments ◽  
E Learning ◽  
Multi Agent ◽  
Learning Research

One of the most closely investigated topics in e-learning research has always been the effectiveness of adaptive learning environments. The technological evolutions that have dramatically changed the educational world in the last six decades have allowed ever more advanced and smarter solutions to be proposed. The focus of this paper is to depict the three main dimensions that have driven research in the e-learning field and the evolution of the technological approaches adopted for the purposes of building advanced educational environments for distance learning. Then, the three different approaches adopted by the authors are discussed; these consist of a multi-agent system, an adaptive SCORM compliant package and an e-learning recommender system.

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