Research Proposal
Pang Wei; Ph. D Proposal; Dept. of Computer Science,University of Maryland, College Park.
(I) Proposed Title
(II) Introduction
(III) Brief Literature Review
(IV) Methodology
(V) Proposed Research Time-Table
(VI) References
(I) Proposed Title
Agent Based Simulation and Its Application in Computational Economics
(II) Introduction
Complex Systems
The definition of complex systems provides a new unity of approach to many different problems. These concepts originate from efforts to understand physical, biological and social systems. Examples of applications can be found in all fields and professions including science, medicine, engineering, management and education. It should bepointed out that complex systems is an active field and the most exciting discoveries are yet to be made. Numerous complex systems are vital to human beings such as market economics, social systems, immune system and etc. So it is important to understand and analyze them well.
The Agent System and Agent Based Simulation
The general evolving agent system is made up of many autonomous agents and each agent can interact with others. Given certain initial conditions, the agent system begins to evolve without external intervention. After several iterations, some meaningful results could be found in this closed system. So the agent based simulation is utilized to investigate the common encountered complex systems especially the social and economical systems.
Agent based Computational Economics
ACE (Agent-based Computational Economics) is a brand new cross research area of economics and computational intelligence. It is the computational study of economies modeled as evolving systems of autonomous interacting agents. Decentralized market economiesare complex systems, and the agents might represent people, companies interacting in market environment composed of resources, trading protocols, technology level, etc.
Economics is a well developed discipline; economists employed a lot of methods to study this field. In the past 10 years, with the quick development of computing science and technology, some economists used a new technique—constructed method from bottom to up implemented by agents simulating economic entries' action in markets. This gave us a new way to explore the distributed market economies and make made an in-depth study of the other complex systems. More detailed description about computational economics can be seen in the following website: wuecon.wustl.edu/sce/
(III) Brief Literature Review
Robert Axelrod's work
The work of Axelrod can be considered as the preliminary research on in the area of agent based social simulation.
In Axelrod's book the Evolution of Cooperation [1], the author discussed how cooperation can emerge in a world of self-seeking egoists--whether superpowers, businesses, or individuals--when there is no central authority to police their actions. The latter book [2] continues the study and pointed out the complexity of the cooperation between interacting agents through gathering together the myriad fruits of a decade's previous work and carefully modified his initial model in the first book.
One of the most exciting aspects is that the author tried to apply the idea of evolutionary computation to the agent based simulation. The simulation environment was looked viewed as an evolving system. The most common used evolutionary algorithm-Genetic Algorithm was employed in the environment to investigate the old classic problem: iterated prisoner's dilemma problem.
This inspires us that the computational intelligence theory can be applied to the evolving agent system and it is helpful to construct the simulation environment and design the culture dish experiment successfully.
Leigh Tesfatsion's work
The work of Leigh Tesfatsion made a major contribution to agent based computational economics by developing the culture dish approach to construct an agent system and to explore the hidden rules among the interacting agents. She summarized the main research areas in ACE: (i) Learning and the embodied mind; (ii) evolution of behavioral norms; (iii) bottom-up modeling of market processes; (iv) formation of economic networks; (v) modeling of organizations; (vi) design of computational agents for automated markets; (vii) parallel experiments with real and computational agents; and (viii) building ACE computational laboratories.
Tesfatsion illustrated that current ACE research divides roughly into four strands differentiated by objective:
1.One primary objective is empirical understanding: Why have particular macro regularities evolved and persisted, despite the absence of top-down planning and control?
2. A second primary objective is normative understanding: How can agent-based models be used as laboratories for the discovery of good economic designs?
3.A third primary objective is qualitative insight and theory generation: How can the full potentiality of economic systems be better understood through a better understanding of their complete phase portraits (equilibria plus basins of attraction)?
4.A fourth primary objective is methodological advancement: How best to provide ACE researchers with the methods and tools they need to undertake the rigorous study of economic systems through controlled computational experiments?
The study of Complex Network and Social Network
Recently, the theory of complex network [6] is developed quickly because of the emergence of many new type complex network systems and the recognition of numerous classic complex systems which can be seen as a complex network. Complex weblike structures describe a wide variety of complex systems of high technological and intellectual importance such as Internet.
The human social network can be seen as a complex network on which fads and ideas spread. The nodes of the social network are human beings and edges represent various social relationships. Social network analysis (SNA) [7] is focused on uncovering the patterning of people's interaction.
Motivated by the above research and recognition, some quantities and measures which embody the complex network theory and SNA may be proposed and investigate in depth in the field of economics together with the agent based simulation.
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