Insuring Risk-Averse Agents

Abstract. In this paper we explicitly model risk aversion in multiagent interactions. We propose an insurance mechanism that be can used by risk-averse agents to mitigate against risky outcomes and to improve their expected utility. Given a game, we show how to derive Pareto-optimal insurance policies, and determine whether or not the proposed insurance policy will change the underlying dynamics of the game (i.e., the equilibrium). Experimental results indicate that our approach is both feasible and effective at reducing risk for agents.

• Type: Conference
• Year: 2009
• Where: ALDT
• Authors: Greg Hines, Kate Larson
• Keywords: ALDT 2009, Algorithmic Decision Theory, Pareto-optimal Insurance Policies, Risk Aversion, Risk-averse Agents