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

Hao Li, Ting Pang, Yuying Wu, Guorui Jiang

2014

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.

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