(IV) Methodology
Model Construction
Simulation Approach
 Our research group is working on an ACE model now. Our main goal is to research behavior of exchange between agents with various product ability and different utility functions. This model is inspired by reference [4], [5], we just considered commodity exchange in a simple simulation society. Commodity exchange is a basic economics behavior, and is the origin of market economies, so it is valuable for economics research. Only considering commodity exchange is important to make our model not too complex to be implemented. We hope some valuable patterns could be found in our simulation by this model. The focus of the research is how exchange improves overall welfare, how exchange cost affects exchange, etc.
   Basing on this simple model, more complex model could be built by carefully inserting additional constraints and conditions. Once a specified model has been constructed, specified phenomenon could be observed and interesting patterns could be found.
   We intend to use the Darwin's evolutionary theory and natural selection mechanisms to make the agents cope with the artificial simulation system. The detailed design for the simulation model may be done in the future work.
Complex Network Analysis Approach
  As we have mentioned before, the analysis method of complex network could be applied to the agent based simulation environment. Each agent can represent a node in the complex network, what will happen if the agents possess the characters properties of the node in the network? On the other hand, whether the agent based simulation environment can be seen as a complex network if we add some rules and constraints? Is the virtual market economics environment also a kind of complex network such as small world network, evolving network or even scale free network [6] if specified conditions are satisfied? The above considerations are significant questions and valuable to study and verify.
Data Collection and Analysis
   Currently the initial model has been constructed and some rough data can be reported. In the future work, the data format should be standardized and some visualized results will be presented before the modelers. With these useful data collected from the framework which is based on the model we have proposed, some algorithms and analysis methods can be utilized to find significant rules. For instance, the whole evolving procedure of the agent system can be recorded to a file and we can clearly see the variation of the agent and the tendency of the overall system at a specified time or iteration.

Verification and Conclusion
Once we had drawn some conclusions which we considered as an important theory, we have to testify our theory and hypothesis by some certain methods. The methods could include both the established theory proven one or the real experiment one. The newly developed Experimental Economics may also provide us an efficient solution, but the concrete deployment steps will be a challenge question and much work should be done.
On the other hand, the theory which was tested to be validate can guide the real market economics and other aspects in the economics, thus to make us better understand the hidden rules in the macro economical environment. This is the ultimate goal of the agent based simulation on Computational Economics.
(V) Proposed Research Time-Table
Sept 2005----Apr 2006 : - Literature review, familiar with the related research area, Obtain a comprehensive knowledge on Agent based social simulation.
May 2006----Jun 2007 -Field Work- model Design: First propose some hypothesis model, and then discuss the validity of the model in the theory aspect. Design the necessary algorithms, analysis the complexity of the model.
Jul 2007----Sept 2007: - Field Work - Construct the model. While studying the proposed models, construct some potential excellent models, coding and testing.
Oct 2007---Nov 2007: - Field Work- Data Analysis: Modify and perfect the model, in the same time collect the data from the already build model, acquire useful information, and then preprocess, analysis and visualize the data by certain techniques thus to find useful patterns and rules.
Dec 2007----Feb 2008: - Field Work – Model Verification: testify the model by theory, real world or experiment. Summarize the results.
Mar 2008----Aug 2008 : - Write the Thesis
(VI) References
[1]Agent-Based Computational Economics, LEIGH TESFATSION, http://www.econ.iastate.edu/tesfatsi/ ,ISU Economics Working Paper No. 1, Revised August 24, 2003
[2] Evolution of Cooperation, Robert M. Axelrod, PrincetonUniversity Press, Princeton, New Jersey, ISBN: 0465021220
[3] The complexity of cooperation-Agent Based Models of Competition and Collaboration, Princeton University Press, Princeton, New Jersey, ISBN: 0691015678
[4] Learning to speculate: Experiments with artificial and real agents, John Duffy,Journal of Economic Dynamics and Control ,Volume 25, Issues 3-4 , March 2001, Pages 295-319
[5]On Money as a Medium of Exchange,Kiyotaki, Nobuhiro Wright, Randall,Journal of Political Economy,Volume (Year): 97 (1989),Pages: 927-954
[6] Statistical mechanics of complex networks, Reka Albert, Albert-Laszlo Barabasi,Reviews of Modern Physics 74, 47 (2002)
[7] Introduction to Social Network Methods, Robert A.Hanneman, faculty.ucr.edu/~hanneman/SOC157/NETTEXT.PDF