Neuroeconomics and Agent-Based Computational Economics

Neuroeconomics and Agent-Based Computational Economics

Shu-Heng Chen
Copyright: © 2014 |Pages: 20
DOI: 10.4018/ijabe.2014040102
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Recently, the relation between neuroeconomics and agent-based computational economics (ACE) has become an issue concerning the agent-based economics community. Neuroeconomics can interest agent-based economists when they are inquiring for the foundation or the principle of the software-agent design. It has been shown in many studies that the design of software agents is non-trivial and can determine what will emerge from the bottom. Therefore, it has been quested for rather a period regarding whether anyone can sensibly design these software agents, including both the choice of software agent models, such as reinforcement learning, and the parameter setting associated with the chosen model, such as risk attitude. In this paper, the author will start a formal inquiry by focusing on examining the models and parameters used to build software agents.
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2. Preference

“The nature of wealth and value is explained by the consideration of an infinitely small amount of pleasure and pain, just as the theory of statics is made to rest upon the equality of indefinitely small amounts of energy. (Jevons, 1879, p. 44; Italics, added)”

Standard economic theory takes individual preferences as given and fixed over the course of the individual's lifetime. It would be hard to imagine how economic models can stand still by giving up preferences or utility functions. They serve as the very foundation of economics just as we quoted above from William Stanley Jevons (1835-1882). Without preference or utility, it will no longer be clear what we mean by welfare, and hence we make welfare-enhancing policy ill-defined. Nevertheless, preference is now in a troubling moment in the development of economics. Even though its existence has been questioned, the development of neuroeconomics may further deepen this turbulent situation.

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