Analyzing Norm Emergence in Communal Sharing via Agent-Based Simulation

This paper describes an agent-based simulation study on the emergence of norms on information communal sharing. To carry out the study, we utilize our simulator TRURL, which (1) contains software agents with decision making and communication functions, and (2) has the capability to evolve artificial societies with specific characteristics defined by a given objective function to be optimized by genetic algorithms. Unlike the literature in social psychology research, which mainly applies evolutionary game theory to homogeneous agents for the simulation, TRURL focuses on the decision making behaviors of heterogeneous agents. Our experimental results have suggested that, contrary to the results of social psychology study so far, for information oriented properties, free riders in the society will not collapse the norm of communal sharing of the properties.