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Authors: Hao Li ; Ting Pang ; Yuying Wu and Guorui Jiang

Affiliation: Beijing University of Technology, China

ISBN: 978-989-758-016-1

Keyword(s): Production-Marketing Collaborative Conflict, Multi-Agent, Self-adaptation Negotiation, RBF Neural Network, Q-reinforcement Learning.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Multi-Agent Systems ; Negotiation and Interaction Protocols ; Software Engineering ; Symbolic Systems

Abstract: In order to overcome the lack of adaptability and learning ability of traditional negotiation, we regard supply chain production-marketing collaborative planning negotiation as the research object, design one five-elements negotiation model, adopt a negotiation strategy based on Q-reinforcement learning, and optimize the negotiation strategy by the RBF neural network and predict the information of opponent for adjusting the concession extent. At last, we give a sample that verifies the negotiation strategy can enhance the ability of the negotiation Agents, reduce the negotiation times, and improve the efficiency of resolving the conflicts of production-marketing collaborative planning, comparing to the un-optimized Q-reinforcement learning.

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Paper citation in several formats:
Li, H.; Pang, T.; Wu, Y. and Jiang, G. (2014). Conflict Resolution of Production-marketing Collaborative Planning based on Multi-Agent Self-adaptation Negotiation.In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-016-1, pages 209-214. DOI: 10.5220/0004830602090214

@conference{icaart14,
author={Hao Li. and Ting Pang. and Yuying Wu. and Guorui Jiang.},
title={Conflict Resolution of Production-marketing Collaborative Planning based on Multi-Agent Self-adaptation Negotiation},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2014},
pages={209-214},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004830602090214},
isbn={978-989-758-016-1},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Conflict Resolution of Production-marketing Collaborative Planning based on Multi-Agent Self-adaptation Negotiation
SN - 978-989-758-016-1
AU - Li, H.
AU - Pang, T.
AU - Wu, Y.
AU - Jiang, G.
PY - 2014
SP - 209
EP - 214
DO - 10.5220/0004830602090214

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