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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/7825

Title: 人工市場アプローチによる介入エージェントを用いた為替介入効果の分析
Authors: 松井, 宏樹
東条, 敏
Keywords: artificial market
multi-agent system
foreign exchange market
reinforcement learning
complex system
Issue Date: 2005
Publisher: 人工知能学会
Magazine name: 人工知能学会論文誌
Volume: 20
Number: 1
Start page: 36
End page: 45
DOI: 10.1527/tjsai.20.36
Abstract: We propose a multi-agent system which learns intervention policies and evaluates the effect of interventions in an artificial foreign exchange market. Izumi et al. had presented a system called AGEDASI TOF to simulate artificial market, together with a support system for the government to decide foreign exchange policies. However, the system needed to fix the amount of governmental intervention prior to the simulation, and was not realistic. In addition, the interventions in the system did not affect supply and demand of currencies; thus we could not discuss the effect of intervention correctly. First, we improve the system so as to make much of the weights of influential factors. Thereafter, we introduce an intervention agent that has the role of the central bank to stabilize the market. We could show that the agent learned the effective intervention policies through the reinforcement learning, and that the exchange rate converged to a certain extent in the expected range. We could also estimate the amount of intervention, showing the efficacy of signaling. In this model, in order to investigate the aliasing of the perception of the intervention agent, we introduced a pseudo-agent who was supposed to be able to observe all the behaviors of dealer agents; with this super-agent, we discussed the adequate granularity for a market state description.
Rights: Copyright (C) 2005 人工知能学会. 松井宏樹, 東条 敏, 人工知能学会論文誌, 20(1), 2005, 36-45.
URI: http://hdl.handle.net/10119/7825
Material Type: publisher
Appears in Collections:b10-1. 雑誌掲載論文 (Journal Articles)

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