Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-26T07:18:55.596Z Has data issue: false hasContentIssue false
  • English
  • Français

Fairness in multi-agent systems

Published online by Cambridge University Press:  01 June 2008

STEVEN DE JONG ,
KARL TUYLS  and
KATJA VERBEECK
STEVEN DE JONG
Affiliation:
MICC, Maastricht University, The Netherlands; e-mail: steven.dejong@micc.unimaas.nl
KARL TUYLS
Affiliation:
MICC, Maastricht University, The Netherlands; e-mail: steven.dejong@micc.unimaas.nl Eindhoven Technical University, The Netherlands; e-mail: k.p.tuyls@tue.nl
KATJA VERBEECK
Affiliation:
Katholieke Hogeschool Sint Lieven, Gent, Belgium; e-mail: katja.verbeeck@kahosl.be
Get access Rights & Permissions [Opens in a new window]

Abstract

Multi-agent systems are complex systems in which multiple autonomous entities, called agents, cooperate in order to achieve a common or personal goal. These entities may be computer software, robots, and also humans. In fact, many multi-agent systems are intended to operate in cooperation with or as a service for humans. Typically, multi-agent systems are designed assuming perfectly rational, self-interested agents, according to the principles of classical game theory. Recently, such strong assumptions have been relaxed in various ways. One such way is explicitly including principles derived from human behavior. For instance, research in the field of behavioral economics shows that humans are not purely self-interested. In addition, they strongly care about fairness. Therefore, multi-agent systems that fail to take fairness into account, may not be sufficiently aligned with human expectations and may not reach intended goals. In this paper, we present an overview of work in the area of fairness in multi-agent systems. More precisely, we first look at the classical agent model, that is, rational decision making. We then provide an outline of descriptive models of fairness, that is, models that explain how and why humans reach fair decisions. Then, we look at prescriptive, computational models for achieving fairness in adaptive multi-agent systems. We show that results obtained by these models are compatible with experimental and analytical results obtained in the field of behavioral economics.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 23 , Issue 2 , June 2008 , pp. 153 - 180
Copyright
Copyright © Cambridge University Press 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aldewereld, H. 2007 Autonomy vs. conformity: an institutional perspective on norms and protocols. PhD thesis, Universiteit Utrecht.Google Scholar
Aristotle. Politics, Book II, Chapter III, 1261b; translated by Benjamin Jowett as The Politics of Aristotle: Translated into English with Introduction, Marginal Analysis, Essays, Notes and Indices, volume 1 of 2. Oxford: Clarendon Press, 1885.Google Scholar
Barabasi, A.-L. and Albert, R. 1999 Emergence of scaling in random networks. Science 286, 509–512.CrossRefGoogle ScholarPubMed
Basu, K. 1994. The traveler’s dilemma: paradoxes of rationality in game theory. American Economic Review 84(2), 391–395.Google Scholar
Basu, K. 2007 The traveler’s dilemma. Scientific American 296(6), 68–73.CrossRefGoogle ScholarPubMed
Bowles, S., Boyd, R., Fehr, E. and Gintis, H. 1997 Homo reciprocans: a research initiative on the origins, dimensions, and policy implications of reciprocal fairness. Advances in Complex Systems 4, 1–30.Google Scholar
Bowling, M. H. and Veloso, M. M. 2002 Multiagent learning using a variable learning rate. Artificial Intelligence 136, 215–250.CrossRefGoogle Scholar
Boyd, R., Gintis, H., Bowles, S. and Richerson, P. 2003 The evolution of altruistic punishment. Proceedings of the National Academy of Sciences of the United States of America 100, 3531–3535.CrossRefGoogle ScholarPubMed
Boyd, R. and Mathew, S. 2007 A narrow road to cooperation. Science 316, 1858–1859.CrossRefGoogle ScholarPubMed
Charness, G. and Rabin, M. 2002 Understanding social preferences with simple tests. Quarterly Journal of Economics 117, 817–869.CrossRefGoogle Scholar
Chevaleyre, Y., Dunne, P. E., Endriss, U., Lang, J., Lema^ıtre, M., Maudet, N., Padget, J., Phelps, S., Rodriguez-Aguilar, J. A. and Sousa, P. 2006 Issues in multiagent resource allocation. Informatica 30, 3–31.Google Scholar
Chevaleyre, Y., Endriss, U., Lang, J. and Maudet, N. 2007 A short introduction to computational social choice. In Proceedings of the 33rd Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM-2007), vol. 4362 of LNCS, Berlin, Heidelberg, Germany: Springer-Verlag, pp. 51–69.Google Scholar
Dannenberg, A., Riechmann, T., Sturm, B. and Vogt, C. 2007 Inequity aversion and individual behavior in public good games: an experimental investigation. SSRN eLibrary.Google Scholar
Dawkins, R. 1976 The Selfish Gene. Oxford: Oxford University Press.Google Scholar
De Jong, S., Tuyls, K. and Sprinkhuizen-Kuyper, I. 2006 Robust and scalable coordination of potential-field driven agents. In Proceedings of IAWTIC/CIMCA 2006, Sydney.CrossRefGoogle Scholar
De Jong, S., Tuyls, K. and Verbeeck, K. 2008a Artificial agents learning human fairness. In Accepted at the International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS’08).Google Scholar
De Jong, S., Tuyls, K., Verbeeck, K. and Roos, N. 2008b Priority awareness: towards a computational model of human fairness for multi-agent systems. Adaptive Agents and Multi-Agent Systems III—Lecture Notes in Artificial Intelligence, 4865.Google Scholar
Denning, D. 1982 Cryptography and Data Security. Boston, USA: Addison-Wesley.Google Scholar
Erev, I. and Roth, A. E. 1998 Predicting how people play games with unique, mixed strategy equilibria. American Economic Review 88, 848–881.Google Scholar
Falk, A. and Fischbacher, U. 2006 A theory of reciprocity. Games and Economic Behavior 54, 293–315.CrossRefGoogle Scholar
Fehr, E. 2004 Don’t lose your reputation. Nature 432, 499–500.CrossRefGoogle ScholarPubMed
Fehr, E. and Gaechter, S. 2000 Fairness and retaliation: the economics of reciprocity. Journal of Economic Perspectives 14, 159–181.CrossRefGoogle Scholar
Fehr, E. and Gaechter, S. 2002 Altruistic punishment in humans. Nature 415, 137–140.CrossRefGoogle ScholarPubMed
Fehr, E. and Schmidt, K. 1999 A theory of fairness, competition and cooperation. Quarterly Journal of Economics 114, 817–868.CrossRefGoogle Scholar
Ferber, J. 1999 Multi-Agent Systems. An Introduction to Distributed Artificial Intelligence. Boston, USA: Addison-Wesley.Google Scholar
Gintis, H. 2001 Game Theory Evolving: A Problem-Centered Introduction to Modeling Strategic Interaction. Princeton, USA: Princeton University Press.Google Scholar
Gueth, W., Schmittberger, R. and Schwarze, B. 1982 An Experimental Analysis of Ultimatum Bargaining. Journal of Economic Behavior and Organization 3(4), 367–388.CrossRefGoogle Scholar
Hamilton, W. 1964 The genetical evolution of social behaviour I and II. Journal of Theoretical Biology 7, 1–16, 17–52.CrossRefGoogle Scholar
Hardin, G. 1968 The tragedy of the commons. Science 162, 1243–1248.CrossRefGoogle ScholarPubMed
Hauert, C., Monte, S. D., Hofbauer, J. and Sigmund, K. 2002 Volunteering as red queen mechanism for cooperation in public goods games. Science 296, 1129–1132.CrossRefGoogle ScholarPubMed
Hauert, C., Traulsen, A., Brandt, H., Nowak, M. and Sigmund, K. 2007 Via freedom to coercion: the emergence of costly punishment. Science 316, 1905–1907.CrossRefGoogle ScholarPubMed
Henrich, J. 2004 Cultural group selection, coevolutionary processes and large-scale cooperation. Journal of Economic Behavior and Organization 53, 3–35.CrossRefGoogle Scholar
Henrich, J. and Boyd, R. 2001 Why people punish defectors. Journal of Theoretical Biology 208, 79–89.CrossRefGoogle ScholarPubMed
Henrich, J., Boyd, R., Bowles, S., Camerer, C., Fehr, E. and Gintis, H. 2004 Foundations of Human Sociality: Economic Experiments and Ethnographic Evidence from Fifteen Small-Scale Societies. Oxford: Oxford University Press.CrossRefGoogle Scholar
Henrich, J., McElreath, R., Barr, A., Ensimger, J., Barrett, C., Bolyanatz, A., Cardenas, J. C., Gurven, M., Gwako, E., Henrich, N. et al. 2006 Costly punishment across human societies. Science 312, 1767–1770.CrossRefGoogle ScholarPubMed
Jackson, M. 2000 Mechanism Theory. Humanities and Social Sciences October, 228–277.Google Scholar
Jennings, N., Sycara, K. and Wooldridge., M. 1998 A roadmap of agent research and development. Autonomous agents and Multi-Agent Systems 1, 275–306.Google Scholar
Kalagnanam, J. and Parkes, D.C. 2004 Auctions, bidding and exchange design. In Simchi-Levi, D., Wu, S. D. and Shen, M. (eds.), Handbook of Quantitative Supply Chain Analysis: Modeling in the E-Business Era, International Series in Operations Research and Management Science, ch. 5. Dordrecht, Netherlands: Kluwer Academic Publishers, pp. 1–84.Google Scholar
Kalisch, G., Milnor, J., Nash, J. and Nering, E. 1952 Some experimental n-person games. Technical report, The Rand Corporation U.S. Air Force.Google Scholar
Keller, L. and Ross, K. G. 1998 Selfish genes: a green beard in the red fire ant. Nature 394 (6693), 573–575.CrossRefGoogle Scholar
Knoch, D., Pascual-Leone, A., Meyer, K., Treyer, V. and Fehr, E. 2006 Diminishing reciprocal fairness by disrupting the right prefrontal cortex. Science 314, 829–832.CrossRefGoogle ScholarPubMed
Leimar, O. and Hammerstein, P. 2001 Evolution of Cooperation through Indirect Reciprocity. Proceedings: Biological Sciences 268(1468), 745–753.Google ScholarPubMed
Lotem, A., Fishman, M. and Stone, L. 1999 Evolution of Cooperation between individuals. Nature 400, 226–227.CrossRefGoogle ScholarPubMed
Mao, X., ter Mors, A., Roos, N. and Witteveen, C. Agent-based scheduling for aircraft deicing. In Schobbens, P.-Y., Vanhoof, W. and Schwanen, G. (eds.) Proceedings of the 18th Belgium–Netherlands Conference on Artificial Intelligence, BNVKI, October 2006. pp. 229–236.Google Scholar
Maynard-Smith, J. 1982 Evolution and the Theory of Games. Cambridge University Press.CrossRefGoogle Scholar
Milinski, M., Semmann, D. and Krambeck, H. 2002 Reputation helps solve the tragedy of the commons. Nature 415, 424–426.CrossRefGoogle ScholarPubMed
Narendra, K. and Thathachar, M. 1989 Learning Automata: An introduction. Boston, USA: Prentice-Hall International.Google Scholar
Nash, J. 1950a Equilibrium points in N-person games. Proceedings of the National Academy of Sciences of the United States of America 36, 48–49.CrossRefGoogle ScholarPubMed
Nash, J. 1950b The bargaining problem. Econometrica 18, 155–162.CrossRefGoogle Scholar
North, D. 1990 Institutions, Institutional Change and Economic Performance. 1st edn., Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Nowak, M., Page, K. and Sigmund, K. 2000 Fairness versus reason in the Ultimatum Game. Science 289, 1773–1775.CrossRefGoogle ScholarPubMed
Nowak, M., Sasaki, A., Taylor, C. and Fudenberg, D. 2004 Emergence of cooperation and evolutionary stability in finite populations. Nature 428, 646–650.CrossRefGoogle ScholarPubMed
Nowak, M. A. and Sigmund, K. 1998 Evolution of indirect reciprocity by image scoring. Nature 393(6685), 573–577.CrossRefGoogle ScholarPubMed
Nowak, M. A. and Sigmund, K. 2005 Evolution of indirect reciprocity. Nature 437(7063),1291–1298.CrossRefGoogle ScholarPubMed
Nydegger, R. and Owen, H. 1974 Two-person bargaining, an experimental test of the Nash axioms. International Journal of Game Theory 3, 239–250.CrossRefGoogle Scholar
Oosterbeek, H., Sloof, R. and van de Kuilen, G. 2004 Cultural differences in ultimatum game experiments: evidence from a meta-analysis. Experimental Economics 7, 171–188.CrossRefGoogle Scholar
Osborne, J. and Rubinstein, A. 1994 A Course in Game Theory. Boston, USA: MIT Press.Google Scholar
Panchanathan, K. and Boyd, R. 2004 Indirect reciprocity can stabilize cooperation without the second-order free rider problem. Nature 432, 499–502.CrossRefGoogle ScholarPubMed
Parkes, D. C. 2008 Computational Mechanism Design. In Lecture notes of Tutorials at 10th Conference. on Theoretical Aspects of Rationality and Knowledge (TARK-05). Institute of Mathematical Sciences, University of Singapore.Google Scholar
Preist, C. and van Tol, M. 1998 Adaptive agents in a persistent shout double auction. In ICE ’98: Proceedings of the First International Conference on Information and Computation Economies, New York: ACM Press, pp. 11–18.Google Scholar
Rabin, M. 1993 Incorporating Fairness into Game Theory and Economics. American Economic Review 83, 1281–1302.Google Scholar
Rodriguez-Aguilar, J. A. 2003 On the design and construction of agent-mediated electronic institutions. PhD thesis, Monografies de l’Institut d’Investigaci´o en Intellig`encia Artificial.Google Scholar
Roth, A. and Malouf, M. 1979 Game theoretic models and the role of information in bargaining. Psychological Review 86, 574–594.CrossRefGoogle Scholar
Sanfey, A. G., Rilling, J. K., Aronson, J. A., Nystrom, L. E. and Cohen, J. D. 2003 The neural basis of economic decision-making in the ultimatum game. Science 300, 1755–1758.CrossRefGoogle ScholarPubMed
Santos, F. and Pacheco, J. 2005 Scale-free networks provide a unifying framework for the emergence of cooperation. Physical Review Letters 95, 98–104.CrossRefGoogle ScholarPubMed
Santos, F., Pacheco, J. and Lenaerts, T. 2006a Emergence of cooperation in heterogeneous structured populations. Proceedings of the 10th International Conference on the Simulation and Synthesis of Living Systems (Alife X). 432–437.Google Scholar
Santos, F., Pacheco, J. and Lenaerts, T. 2006b Evolutionary dynamics of social dilemmas in structured heterogeneous populations. Proceedings of the National Academy of Sciences of the United States of America 103, 3490–3494.CrossRefGoogle ScholarPubMed
Santos, F., Pacheco, J. and Lenaerts, T. 2006c Cooperation prevails when individuals adjust their social ties. PLoS Computational Biology 2(10),1284–1291.CrossRefGoogle ScholarPubMed
Scott, W. 2001 Institutions and Organizations, 2 edn. Thousand Oaks, USA: Sage.Google Scholar
Sen, S. and Airiau, S. 2007 Emergence of norms through social learning. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence pp. 1507–1512.Google Scholar
Shoham, Y., Powers, R. and Grenager, T. 2007 If multi-agent learning is the answer, what is the question?. Artificial Intelligence 171(7),365–377.CrossRefGoogle Scholar
Sigmund, K., Hauert, C. and Nowak, M. 2001 Reward and punishment. Proceedings of the National Academy of Sciences of the United States of America 98(19), 10757–10762.CrossRefGoogle ScholarPubMed
Simon, H. 1957 Models of Man. London, UK: John Wiley.Google Scholar
Simon, H. 1972 Theories of Bounded Rationality. Decision and Organization 1, 161–176.Google Scholar
Simon, H. and Newell, A. 1972 Human Problem Solving. Englewood Cliffs, USA: Prentice Hall.Google Scholar
Sugden, R. 1986 The Economics of Rights, Co-operation and Welfare. Oxford: Basil Blackwell.Google Scholar
Thathachar, M. and Sastry, P. 2004 Networks of Learning Automata: Techniques for Online Stochastic Optimization. Dordrecht, Netherlands: Kluwer Academic Publishers.CrossRefGoogle Scholar
Tuyls, K. and Nowe, A. 2005 Evolutionary game theory and multi-agent reinforcement learning. The Knowledge Engineering Review 20(01), 63–90.CrossRefGoogle Scholar
Van Huyck, J., Battalio, R., Mathur, S. and Ortmann, A. 1995 On the origin of convention: evidence from symmetric bargaining games. International Journal of Game Theory 34, 187–212.CrossRefGoogle Scholar
Vaughn, K. L. 1987 The New Palgrave: A Dictionary of Economics, vol. 2. ch. Invisible Hand. London, UK: Macmillan.Google Scholar
Vazquez-Salceda, J., Aldewereld, H. and Dignum, F. 2005 Norms in multiagent systems: from theory to practice. Computer Systems Science and Engineering 20(4),225–236.Google Scholar
Verbeeck, K., Now´e, A., Parent, J. and Tuyls, K. 2007 Exploring selfish reinforcement learning in repeated games with stochastic rewards. Journal of Autonomous Agents and Multi-Agent Systems 14, 239–269.CrossRefGoogle Scholar
von Neumann, J. and Morgenstern, O. 1944 Theory of Games and Economic Behaviour. Princeton, USA: Princeton University Press.Google Scholar
Wedekind, C. and Milinski, M.Cooperation through image scoring in humans. Science 288(5467), 850–852.CrossRefGoogle Scholar
Weiss, G. 1999 Multiagent Systems. A Modern Approach to Distributed Artificial Intelligence. Boston, USA: MIT Press.Google Scholar
Weyns, D., Boucke, N., Holvoet, T. and Schols, W. 2005 Gradient field-based task assignment in an AGV transportation system. In Proceedings of EUMAS pp. 447–458.Google Scholar
Yaari, M. and Bar-Hillel, M. 1981 On dividing justly. Social Choice and Welfare 1, 1–24.CrossRefGoogle Scholar
Yamagishi, T. 1986 The provision of a sanctioning system as a public good. Journal of Personality and Social Psychology 51(1),110–116.CrossRefGoogle Scholar
Zollman, K. J. 2008 Explaining fairness in complex environments. Politics, Philosophy, and Economics 7(1),81–97.CrossRefGoogle Scholar