NDLI: Analyzing the Evolution of Social Exchange Strategies in Social Preference-Based MAS through an Evolutionary Spatial Approach of the Ultimatum Game

Content Provider	IEEE Xplore Digital Library
Author	Macedo, L.F.K. Dimuro, G.P. Aguiar, M.S. Costa, A.C.R. Mattos, V.L.D. Coelho, H.
Copyright Year	2012
Abstract	This paper presents a multiagent-based approach of an evolutionary and spatial version of the Ultimatum Game interpreted as Game of Social Exchange Processes, where the agents organized in a complex network evolve their exchange strategies considering their possibly different social preferences. We analyze the possibility of the emergence of the equilibrium/fairness behavior when the agents, trying to maximize their social preference-based utility functions, increase the number of successful interactions. We consider an incomplete information game, since the agents do not have information about the other agents' exchange strategies. For the strategy learning process, a genetic algorithm is used, where the agents aiming at the self-regulation of the exchanges allowed by the game, balance individual and collective goals expressed by their social preferences. We also analyze a second type of scenario, considering an influence politics, when the average of the offer and reserve values of all agents adopting the same social preference form becomes public in a single simulation step, and the agents of the same network, have been influenced by that, imitate those values. At the same time, the network topology is modified, representing some kind of mobility, in order to analyze if the results are dependent on the neighborhood. The model was implemented in Net Logo.
Starting Page	83
Ending Page	90
File Size	2543410
Page Count	8
File Format	PDF
ISBN	9781467356732
DOI	10.1109/BWSS.2012.26
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-20
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Analytical models Evolutionary Spatial Games Hidden Markov models Ultimatum Game Games Materials Complex networks Social Exchange Strategies Vectors Social Preference-based MAS Genetic algorithms
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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