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.
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References
Arrow, K.: Essays in the Theory of Risk-Bearing. North-Holland, Amsterdam (1971)
Arrow, K., Debreu, G.: Existence of an equilibrium for a competitive economy. Econometrica 22(3), 265–290 (1954)
Borch, K.: The Mathematical Theory of Insurance. Lexington Books (1974)
Swiss Reinsurance Company. World insurance in 2006: Premiums came back to “life” (2006)
Conitzer, V., Sandholm, T.: AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents. Machine Learning 67(1-2), 23–43 (2006)
Goeree, J.K., Holt, C.A., Palfrey, T.R.: Risk averse behavior in generalized matching pennies games. Games and Economic Behavior 45(1), 97–113 (2003)
Lam, Y.-H., Zhang, Z., Ong, K.-L.: Insurance Services in Multi-agent Systems. In: Zhang, S., Jarvis, R.A. (eds.) AI 2005. LNCS (LNAI), vol. 3809, pp. 664–673. Springer, Heidelberg (2005)
Mas-Colell, A., Whinston, M., Green, J.R.: Microeconomic Theory. Oxford University Press, Oxford (1995)
Page, F.H.: Optimal auction design with risk aversion and correlated information. Technical report, Tilburg University (1994)
Papadimitriou, C.H., Roughgarden, T.: Computing correlated equilibria in multi-player games. Journal of the ACM 55(3) (2005)
Rabin, M.: Risk aversion and expected-utility theory: A calibration theorem. Econometrica 68, 1281–1292 (2000)
Raviv, A.: The design of an optimal insurance policy. The American Economic Review 69, 84–96 (1979)
Robu, V., Poutré, H.L.: Designing bidding strategies in sequential auctions for risk averse agents: A theoretical and experimental investigation. In: Proceedings of the 9th Workshop on Agent Mediated Electronic Commerce, Honolulu, USA, pp. 76–89 (2007)
Rothschild, M., Stiglitz, J.: Equilibrium in competitive insurance markets: An essay on the economics of imperfect information. The Quarterly Journal of Economics 90, 629–649 (1976)
Rozenfeld, O., Tennenholtz, M.: Routing mediators. In: Proceedings of IJCAI 2007, Hyderabad, India, pp. 1488–1493 (2007)
Shoham, Y., Powers, R., Grenager, T.: If multiagent learning is the answer, what is the question? Artificial Intelligence 171(7), 365–377 (2007)
Stiglitz, J.: Nobel lecture (2001), http://nobelprize.org/nobel_prizes/economics/laureates/2001/stiglitz-lecture.pdf
Tversky, A., Kahneman, D.: Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty 5(4), 297–323 (1992)
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Hines, G., Larson, K. (2009). Insuring Risk-Averse Agents. In: Rossi, F., Tsoukias, A. (eds) Algorithmic Decision Theory. ADT 2009. Lecture Notes in Computer Science(), vol 5783. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04428-1_26
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DOI: https://doi.org/10.1007/978-3-642-04428-1_26
Publisher Name: Springer, Berlin, Heidelberg
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