Abstract
In this paper, the role of incentives in social order is questioned, based on a notion of incentive as additional individual utility, provided by an external entity, to actions achieving global utility. Two notions of norms are compared: (1) inputs which modify agents’ decisions through incentives (sanctions) and (2) prescriptions to execute obligatory action for intrinsic motivations. Two types of agents which reason upon norms are also compared: (1) incentive based rational deciders, and (2) normative agents which are prescribed to execute norms for intrinsic reasons. The two types of agents are expected to have a different impact on norm compliance. Under suboptimal conditions of application of sanctions (uncertian punishment), transgression is expected to propagate more easily and rapidly among incentive-based agents than among normative agents. In particular, incentive-based agents are expected to show a fast decline and even a collpase in compliance with the norms. Normative agents are expected to exhibit an oscillating behaviour, or at least a graceful degradation of compliance. Finally, the role of incentives is shown to have a lesser impact on natural social agents than expected by a model of rational decision. What is worse, incentives have been shown to produce even negative effects on several aspects of social learning and norm compliance.
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References
Bem, D.J. 1972. Self-perception theory. In L. Berkovitz (ed) Advances in Experimental Social Psychology, New York, Academic Press.
Castelfranchi, C. & Conte, R. 1998. Limits of economic rationality for agents and MA systems. Robotics and Autonomous Systems, Special issue on Multi-Agent Rationality, Elsevier Editor, 24, 127–139.
Castelfranchi, C., Miceli, M., Cesta, A. 1992. Dependence Relations among Autonomous Agents. In Y. Demazeau, E. Werner (eds), Decentralized AI - 3, 215–31. Amsterdam: Elsevier.
Cohen, P. R. & Levesque, H. J. 1990b. Persistence, Intention, and Commitment. In P.R Cohen, J. Morgan & M.A. Pollack (eds) Intentions in Communication, 33–71. Cambridge, MA: The MIT Press.
Cohen, Ph. & Levesque, H. 1990a. Intention is choice with commitment. Artificial Intelligence, 42(3), 213–261.
Conte, R. & Castelfranchi, C. 1999. From conventions to prescritions. Towards an integrated view of norms. Artificial Intelligence and Law 7, 323–340.
Conte, R. & Castelfranchi, C. 1995a. Cognitive and social action. London: UCL Press.
Conte, R., Miceli, M., Castelfranchi, C, 1991. Limits and Levels of Cooperation. Disentangling Various Types of Prosocial Interaction. In Y. Demazeau, J.P. Mueller (eds), Decentralized AI-2, 147–157. Armsterdam: Elsevier.
Crabtree, B. 1998. What Chance Software Agents, The Knowledge Engineering Review, 13, 131–137.
Greene, D., Sternberg, B., and Lepper, M.R., 1976. Overjustification in a Token Economy. Journal of Personality and Social Psychology, 57: 41–54.
Hennessey, B.A. & Zbikowski, S.M. 1993. Immunizing children against the negative effects of reward: A further examination of intrinsic motivation focus sessions, Creativity Research Journal, 6, 297–307.
Jennings N. 1995. Commitment and Conventions: the foundation of coordination in multi-agent systems. The Knowledge Engineering Review, 8.
Jennings, N. R. & Campos, J.R. 1997. Towards a social level characterisation of socially responsible agents, IEE Proceedings on software engineering 144(1), 11–25.
Jennings, N. R. & Mandami, E. H. 1992. Using joint responsibility to coordinate collaborative problem solving in dynamic environments. In Proceedings of the 10th National Conference on Artificial Intelligence, San Mateo, CA: Kaufmann, 269–275.
Jones A.J.I & Pörn, I., 1991. On the Logic of Deontic Conditionals. In J.J.C. Meyer, R.J. Wieringa (eds), First International Workshop on Deontic Logic in Computer Science, 232–47.
Kinny, D. & Georgeff, M. (1994). Commitment and effectiveness of situated agents. In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, IJCAI-93, Sydney, 82–88.
Lepper, M.R. (forthcoming) Theory by numbers? Some concerns about meta-analysis, Applied Cognitive Psychology
Rao, A.S. 1998. A Report on Expert Assistants at the Autonomous Agents Conference. The Knowledge Engineering Review, 13, 175–1179.
Shoham, Y. & Tennenholtz M. 1992. On the synthesis of useful social laws in artificial societies. Proceedings of the 10th National Conference on Artificial Intelligence, San Mateo, CA: Kaufmann, 276–282.
Tang, S. & Hall, V.C. (forthcoming) The overjustification effect: A meta-analysis, Applied Cognitive Psychology
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Conte, R., Castelfranchi, C. (2001). Are Incentives Good Enough to Achieve (Info) Social Order?. In: Conte, R., Dellarocas, C. (eds) Social Order in Multiagent Systems. Multiagent Systems, Artificial Societies, and Simulated Organizations, vol 2. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1555-5_3
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DOI: https://doi.org/10.1007/978-1-4615-1555-5_3
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