Social Simulation with Both Human Agents and Software Agents: An Investigation into the Impact of Cognitive Capacity on Their Learning Behavior

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Author(s): Shu-Heng Chen (National Chengchi University, Taiwan), Chung-Ching Tai (Tunghai University, Taiwan), Tzai-Der Wang (Cheng Shiu University, Taiwan)and Shu G. Wang (Chengchi University, Taiwan)
Copyright: 2011
Pages: 22
Source title: Gaming and Simulations: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-60960-195-9.ch318

Keywords: Information Science Reference / Media & Communications / Multimedia Technology

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Abstract

In this chapter, we will present agent-based simulations as well as human experiments in double auction markets. Our idea is to investigate the learning capabilities of human traders by studying learning agents constructed by Genetic Programming (GP), and the latter can further serve as a design platform in conducting human experiments. By manipulating the population size of GP traders, we attempt to characterize the innate heterogeneity in human being’s intellectual abilities. We find that GP traders are efficient in the sense that they can beat other trading strategies even with very limited learning capacity. A series of human experiments and multi-agent simulations are conducted and compared for an examination at the end of this chapter.

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Social Simulation with Both Human Agents and Software Agents: An Investigation into the Impact of Cognitive Capacity on Their Learning Behavior

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