Conflict Resolution of Production-marketing Collaborative Planning based on Multi-Agent Self-adaptation Negotiation

Hao Li, Ting Pang, Yuying Wu, Guorui Jiang

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.

References

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Paper Citation


in Harvard Style

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


in Bibtex Style

@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},
}


in EndNote Style

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