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Application of reinforcement learning in an open railway access market price negotiation

Wong, Shun K., Tsang, Chi W., & Ho, Tin Kin (2008) Application of reinforcement learning in an open railway access market price negotiation. In IEEE International Conference on Systems, Man and Cybernetics, 2008. SMC 2008., IEEE, Singapore, pp. 2309-2314.

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Abstract

In an open railway access market price negotiation, it is feasible to achieve higher cost recovery by applying the principles of price discrimination. The price negotiation can be modeled as an optimization problem of revenue intake. In this paper, we present the pricing negotiation based on reinforcement learning model. A negotiated-price setting technique based on agent learning is introduced, and the feasible applications of the proposed method for open railway access market simulation are discussed.

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ID Code: 38368
Item Type: Conference Paper
Keywords: Reinforcement learning, Machine learning, Railway simulation
DOI: 10.1109/ICSMC.2008.4811637
ISBN: 9781424423835
ISSN: 1062-922X
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Expert Systems (080105)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Simulation and Modelling (080110)
Australian and New Zealand Standard Research Classification > COMMERCE MANAGEMENT TOURISM AND SERVICES (150000) > TRANSPORTATION AND FREIGHT SERVICES (150700) > Rail Transportation and Freight Services (150702)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2008 IEEE
Deposited On: 08 Nov 2010 10:50
Last Modified: 11 Aug 2011 04:23

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