Mathematical foundation for agent based social systems sciences: Reformulation of norm game by social learning dynamics

Authored by H Deguchi

Date Published: 2004

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Abstract

In this paper we investigate a dynamic decision-making model of social learning and its bifurcation analysis that give a mathematical foundation for the research program of agent-based social systems sciences (ABSSS). For the purpose we formulate a non stationary Markov process on the alternatives. Then we introduce a dynamical system called social learning dynamics (SLD). SLD provides a theoretical framework of agent based modeling (ABM) and its simulation. We focus on the concept of indirect control where we control boundary conditions of a system to manage steady state of the system. We also apply SLD to the problem of norm formation and collapsing processes. The model is originally formulated and analyzed by R. Axelrod in the form of agent-based simulation as norm game and meta-norm game. We give a reconstruction of norm and meta-norm game by SLD. We give some propositions for norm game and meta-norm game. As a result we give an answer for second order social dilemma.

Tags

Agent-based modeling agent-based social systems sciences norm game second order social dilemma social learning dynamics