Author(s)

Peter Mitic

Abstract

Consensus and conflict are modelled in the context of interacting pairs of agents who may have very diverging sentiments regarding some particular issue. simulations using the model display character- istics of complexity. Agents are modelled using Beta probability density functions whose parameters determine the agent’s opinion and resistance to change after an interaction, and a third independent parameter that determines the agent’s influence. interactions among groups of agents with both aligned and opposing sentiments are simulated. the results indicate that in most cases a form of consensus is reached eventually, but for opposed agents, it is not possible to tell which agents that consensus will favour. proofs of convergence are given in the cases where the initial state is one of consensus, and when it is one of conflict.

Keywords

Beta distribution, conflict, consensus, convergence, influence, resistance, sentiment, simulation