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How New Individuals Behave in a Heterogeneous Community: A Computational Approach to Norm Assimilation Using Agent-Based Systems

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Abstract

Heterogeneous community entails a number of social groups that adopt similar/different social norms. In such community, new individuals who join a new social group should be able to decide with which group they could assimilate based on their capabilities/values/manners. Otherwise, they would be penalized by other members in the group for violating some norms which they cannot comply. Using this approach, software agents would have better reasoning in simulating human society. In this paper, the authors propose a norms assimilation theory, in which a new agent attempts to assimilate with a social group’s norms. This theory builds an approach to norm assimilation, analyzes the cases for an agent to decide to assimilate with a social group and develops a mathematical model to measure the assimilation cost and the agent’s ability. The approach is developed based on the agent’s internal belief about its ability and desire, and its external belief about the cost of assimilating with a number of social groups. The significance of this research is two-fold. Firstly, the study paves the way to future design of intelligent systems, i.e., software agents or robots, to closely mimic human social interactions. Secondly, the norm assimilation using agent-based system could be potentially utilized to simulate some social issues such as immigrants, new students, expatriate etc. The experiments that have been conducted demonstrate that an agent in the domain is able to calculate the assimilation cost and decide which social group to join.

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Correspondence to Moamin Mahmoud.

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This paper was recommended for publication by Editor DI Zengru.

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Mahmoud, M., Ahmad, M.S., Mostafa, S. et al. How New Individuals Behave in a Heterogeneous Community: A Computational Approach to Norm Assimilation Using Agent-Based Systems. J Syst Sci Complex 33, 849–881 (2020). https://doi.org/10.1007/s11424-020-8097-0

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  • DOI: https://doi.org/10.1007/s11424-020-8097-0

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