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Neural Networks
Bayesian learning in negotiation
International Journal of Human-Computer Studies - Evolution and learning in multiagent systems
Brokerage between buyer and seller agents using constraint satisfaction problem models
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Computer Networks: The International Journal of Computer and Telecommunications Networking
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An Infrastructure for Rule-Driven Negotiating Software Agents
DEXA '01 Proceedings of the 12th International Workshop on Database and Expert Systems Applications
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WETICE '99 Proceedings of the 8th Workshop on Enabling Technologies on Infrastructure for Collaborative Enterprises
An Experience Based Evolutionary Negotiation Model
ICCIMA '03 Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
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A machine-learning approach to automated negotiation and prospects for electronic commerce
Journal of Management Information Systems - Special issue: Information technology and its organizational impact
WebKDD'04 Proceedings of the 6th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
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IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Detecting Unsuccessful Automated Negotiation Threads When Opponents Employ Hybrid Strategies
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Asymmetric negotiation based collaborative product design for component reuse in disparate products
Computers and Industrial Engineering
A multi-agent based system for e-procurement exception management
Knowledge-Based Systems
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CDVE'10 Proceedings of the 7th international conference on Cooperative design, visualization, and engineering
A new mechanism for negotiations in multi-agent systems based on ARTMAP artificial neural network
KES-AMSTA'11 Proceedings of the 5th KES international conference on Agent and multi-agent systems: technologies and applications
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This paper studies an automated negotiation system by means of a learning-based approach. Negotiation between shipper and forwarder is used as an example in which the issues of negotiation are unit shipping price, delay penalty, due date, and shipping quantity. A data ratios method is proposed as the input of the neural network technique to explore the learning in automated negotiation with the negotiation decision functions (NDFs) developed by [Faratin, P., Sierra, C., & Jennings, N.R. (1998). Negotiation Decision Functions for Autonomous Agents. Robotics and Autonomous Systems, 24 (3), 159-182]. The concession tactic and weight of every issue offered by the opponent can be learned from this process exactly. After learning, a trade-off mechanism can be applied to achieve better negotiation result on the distance to Pareto optimal solution. Based on the results of this study, we believe that our findings can provide more insight into agent-based negotiation and can be applied to improve negotiation processes.