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Student Number	91423025
Author	Pi-Fang Chang(張碧方)
Author's Email Address	s1423025@cc.ncu.edu.tw
Statistics	This thesis had been viewed 1008 times. Download 565 times.
Department	Information Management
Year	2003
Semester	2
Degree	Master
Type of Document	Master's Thesis
Language	English
Title	Using Swarm to Build a Multi-Agent Simulation System for Artificial Stock Market
Date of Defense	2004-06-23
Page Count	73
Keyword	Artificial Stock Market Swarm Agent-Based Simu
Abstract	Agent-based simulations of markets have gained more and more acceptance among social scientists in the last decade. The Santa Fe Artificial Stock Market (ASM) is the most well-known one among those computer simulated artificial financial markets. Therefore, there are many researchers to modify the ASM model, but rarely help with the details of designing or building a simulation system for it. There are some efforts supporting the kind of job recently, but they are generally lack of scalability, convenience and friendly user interface of simulation system. Hence, we use Swarm and the idea of MASS-Z to design and implement a multi-agent simulation system, called MASS-S. We propose the architecture of MASS-S and map it to ASM to show how it works. Besides, we also introduce the tool, Swarm, to show how to facilitate it to implement MASS-S. Finally, we design different simulation applications to compare the results of simulations by MASS-S. We believe that it will be a great helpful to researchers to build many kinds of simulation system with an efficient and easy approach, and it will be a contribution to the researchers who aren’t familiar with code writings.
Table of Content	Abstract 摘要 1. Introduction1 1.1 Research Motivation2 1.2 Research Goals2 1.3 Organization of this thesis3 2. Background4 2.1 Artificial Stock Market4 2.1.1 SFI Market Early History4 2.1.2 Structure of the Market5 2.2 Agent-based Simulation Model10 2.3 MASS-Z11 2.3.1 MASS-Z Architecture12 2.3.2 MASS-F13 2.3.3 Multi-Agent Toolkit: ZEUS15 3. Simulation Tool：Swarm18 3.1 Introduction of Swarm18 3.1.1 What is Swarm18 3.1.2 Structure of Swarm19 3.2 What Swarm Provides20 3.3 Important features of Swarm22 3.3.1 Zones23 3.3.2 Collections24 3.3.3 Random25 3.3.4 Activity26 3.3.5 Probes27 3.3.6 GUI Interface28 3.4 Example：Java-ASM29 3.4.1 Sketch of Java-ASM Classes30 3.5 The difference between ZEUS and Swarm34 4. System Design36 4.1 MASS-S System36 4.2 Mapping MASS-S to ASM39 4.2.1 Simulation Time Step39 4.2.2 Forecasting Mechanism42 4.2.3 Learning Mechanism--Genetic Algorithm43 4.2.4 Market Maker46 5. System Implementation and Experiments49 5.1 Using Swarm to build up MASS-S49 5.2 System Implementation52 5.2.1 Environmental Module52 5.2.2 Behavior of Roles Module55 5.2.3 Execution of Simulation Application57 5.3 Experiments59 5.3.1 Simulation Parameters60 5.3.2 Simulation Results60 5.3.3 Discussions66 6. Conclusions67 References69
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Advisor	Shi-Jen Lin(林熙禎)
Files	91423025.pdf approve immediately
Date of Submission	2004-07-12

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