Special session : Agent-based Computational Economics and Experimental Economics
This special session attempts to forge a discussion on the recent developments and the future directions of Agent-Based Computational Economics, in the light of advances in Experimental Economics. In particular, this calls for a greater attention to the design of artificial agents for which the findings from Experimental Economics might prove to be quite insightful.
Agent Based Modeling (ABM) has been steadily gaining more importance in the field of Economics and Finance. It is being viewed as an alternative approach to the conventional equation-based economic modeling, and as a useful methodology to investigate complex systems around us. In its early stages, developments in ABM paralleled those in Computational Intelligence, such as Zero-Intelligence Agents, Cellular Automata, Artificial Neural Networks, Fuzzy Logic, Swarm Intelligence, Genetic Algorithm, and Genetic Programming. It marked a truly interdisciplinary approach to social sciences, drawing insights from a variety of fields such as mathematics, biology, neuroscience, and computer science among others. Today, the development of ABM has reached a stage where the evidence concerning human decision making, largely arising from lab and filed experiments can no longer be neglected if it were to provide a formidable alternative. Among the factors affecting human decision making, cognitive capacity, personality, culture, emotion and social preference are well recognized and documented. However, integrating these attributes within the existing models of artificial agents is far from being trivial.
Why and what human characteristics should be incorporated while designing of artificial agents? How would incorporating these human-like factors into ABM enhance our understanding of the complex social systems? What should be the selection criterion? What are the potential issues in integrating them into existing models of interacting agents? How can we formally translate these diverse, cross-disciplinary notions coherently into the framework of ABM? What are the technical, philosophical and epistemological conundrums that this might entail? These are some of the questions that we aim to address in the special session.
Invited research areas include, but is not limited to, Computational Behavioral Economics, Computational Economics, Experimental Economics, Behavioral Game Theory, Agent-Based Simulation, Bounded Rationality, Social Networks, Computational Psychology.
For submission, please visit http://datamining.it.uts.edu.au/conferences/besc14/ for details.
Session Chair: Ying-Fang Kao (AI-Econ Research Center, National Chengchi University, Taiwan)
Program Committee
Shu-Heng Chen (AI-Econ Research Center, Department of Economics, National Chengchi University, Taiwan)
Bin-Tzong Chie (Tamkang University, Taiwan)
Ye-Rong Du (AI-Econ Research Center, Department of Economics, National Chengchi University, Taiwan)
Chung-Ching Tai (Tunghai Uuniversity, Taiwan)
Zhang Tong (Southwestern University of Finance and Economics, China)
Ragupathy Venkatachalam (Centre for Development Studies, India)