This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Genetic Action Trees A New Concept for Social and Economic Simulation

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Thomas Pitz (Laboratory of Experimental Economics University of Bonn)
Thorsten Chmura (Laboratory of Experimental Economics University of Bonn)

Additional information is available for the following registered author(s):

Abstract

Multi-Agent Based Simulation is a branch of Distributed Artificial Intelligence that builds the base for computer simulations which connect the micro and macro level of social and economic scenarios. This paper presents a new method of modelling the formation and change of patterns of action in social systems with the help of Multi-Agent Simulations. The approach is based on two scientific concepts: Genetic Algorithms [Goldberg 1989, Holland 1975] and the theory of Action Trees [Goldman 1971]. Genetic Algorithms were developed following the biological mechanisms of evolution. Action Trees are used in analytic philosophy for the structural description of actions. The theory of Action Trees makes use of the observation of linguistic analysis that through the preposition by a semi-order is induced on a set of actions. Through the application of Genetic Algorithms on the attributes of the actions of an Action Tree an intuitively simple algorithm can be developed with which one can describe the learning behaviour of agents and the changes in action spaces. Using the extremely simplified economic action space, in this paper called “SMALLWORLDâ€, it is shown with the aid of this method how simulated agents react to the qualities and changes of their environment. Thus, one manages to endogenously evoke intuitively comprehensible changes in the agents‘ actions. This way, one can observe in these simulations that the agents move from a barter to a monetary economy because of the higher effectiveness or that they change their behaviour towards actions of fraud.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://129.3.20.41/eps/comp/papers/0507/0507002.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by EconWPA in its series Computational Economics with number 0507002.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 23 pages
Date of creation: 14 Jul 2005
Date of revision:
Handle: RePEc:wpa:wuwpco:0507002

Note: Type of Document - pdf; pages: 23
Contact details of provider:
Web page: http://129.3.20.41

For technical questions regarding this item, or to correct its listing, contact: (EconWPA).

Related research
Keywords: Multi agent system; genetic algorithms; actiontrees; learning; decision making; economic and social behaviour; distributed artificial intelligence;

Find related papers by JEL classification:
C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

This paper has been announced in the following NEP Reports:

Statistics
Access and download statistics

Did you know? You can use IDEAS to provide links to papers and articles in your course syllabus.

This page was last updated on 2009-11-13.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.