Abstract
The necessity to model the mental ingredients of norm compliance is a controversial issue within the study of norms. So far, the simulation-based study of norm emergence has shown a prevailing tendency to model norm conformity as a thoughtless behavior, emerging from social learning and imitation rather than from specific, norm-related mental representations. In this paper, the opposite stance—namely, a view of norms as hybrid, two-faceted phenomena, including a behavioral/social and an internal/mental side—is taken. Such a view is aimed at accounting for the difference between norms, on one hand, and either behavioral regularities (conventions) on the other. This paper, in particular, is addressed to find out the internal ingredients required for the former distinction, i.e., to model norms as distinct from mere conventions, and defined as behaviors spreading to the extent that and because the corresponding commands and beliefs do spread as well. After a brief presentation of a normative agent architecture, the results of agent-based simulations testing the impact of norm recognition and the role of normative beliefs in the emergence and innovation of social norms are presented and discussed. More specifically, the present work will endeavour to show that a sudden external constraint (e.g. a barrier preventing agents from moving among social settings) facilitates norm innovation: under such a condition, agents provided with a module for telling what a norm is can generate new (social) norms by forming new normative beliefs, irrespective of the most frequent actions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
In a successive work (Shoham and Tennenholtz, 1994), indeed, these authors have introduced the notion of co-learning, which refers to a process in which several agents simultaneously try to adapt to one another’s behavior so as to produce desirable global system properties. Of particular interest are two specific co-learning settings, which relate to the emergence of conventions and the evolution of cooperation in societies, respectively. Despite the indubitable significance of this work, the treatment of norms as emerging conventions resulting from co-learning processes, can only deal with how preexisting actions are gradually generalized or dropped.
Throughout the paper, we will speak of goals from the point of view of computer science and autonomous agent theory. In particular, a goal is a wanted world-state that triggers and guides action (Conte 2009).
For example, Posner and Rasmusen (1999) cope with the creation and destruction of norms, but with special reference to sanctions. The issue is certainly not uninteresting, but for the aim of this paper we prefer to focus just on detecting which are the cues that lead an agent to interpret a social behavior as normative, putting for the moment aside questions about sanctions and enforcement mechanisms.
At the moment, the normative beliefs’ salience can only increase, depending on how many instances of the same normative belief are stored in the Normative Board. This feature has the negative effect that some norms become highly salient, exerting an excessive interference with the decisional process of the agent. We are now improving the model, adding the possibility that, if the normative belief is inactive for a certain amount of time, its salience will decrease.
It has to be said that the input we have modelled is far from accounting for the extraordinary complexity of norms.
References
Alchourròn CE, Bulygin E (1971) Normative systems. Springer, Wien
Alchourròn CE, Gardernfors P, Makinson D (1985) On the logic of theory change: partial meet contraction and revision functions. J Symbolic Logic 50:510–530
Andrighetto G, Campenni' M, Conte R, Paolucci M (2007) On the immergence of norms: a normative agent architecture. In: Proceedings of AAAI symposium, social and organizational aspects of intelligence Washington, DC
Andrighetto G, Campenni' M, Cecconi F, Conte R (2008) How agents find out norms: a simulation based model of norm innovation. In: 3rd international workshop on normative multiagent systems (NorMAS 2008)
Axelrod R (1986) An evolutionary approach to norms. Am Polit Sci Rev 4(80):1095–1111
Axelrod R (1987) The evolution of strategies in the iterated prisoner’s dilemma. Kaufmann, Los Altos
Bicchieri C (2006) The grammar of society: the nature and dynamics of social norms. Cambridge University Press, New York
Binmore K (1994) Game-theory and social contract. vol 1: fair playing. Clarendon, Cambridge
Boella G (2001) Social order in multiagent systems, chapter deliberate normative agents. basic instructions. Kluwer, Norwell
Boella G, van der Torre L, Verhagen H (2006) Special issue edited by normative multiagent systems. J Comput Math Organ Theory (CMOT) 12:2–3
Broersen J, Dastani M, Hulstijn J, Huang Z, van der Torre L (2001) The BOID architecture: conflicts between beliefs, obligations, intentions and desires. In: Proceedings of the 5th international conference on Autonomous Agents, Montreal, Quebec, Canada, pp 9–16
Broersen J, Dastani M, van der Torre L (2005) Beliefs, obligations, intentions, and desires as components in an agent architecture. Int J Intell Syst 20(9):893–920
Castelfranchi C (1998) Simulating with cognitive agents: the importance of cognitive emergence. Multi-agent systems and agent-based simulation. Springer, Berlin
Castelfranchi C (1999) Prescribed mental attitudes in goal-adoption and norm-adoption. Artif Intell Law 7(1):37–50
Castelfranchi C, Conte R (1999) From conventions to prescriptions: towards a unified theory of norms. AI Law 7:323–340
Conte R, Castelfranchi C (1995) Cognitive and social action. University College of London Press, London
Conte R, Castelfranchi C (2006) The mental path of norms. Ratio Juris 19(4):501–517
Conte R, Dignum F (2001) From social monitoring to normative influence. J Artif Soc Soc Simul 4(2)
Conte R, Castelfranchi C, Dignum F (1998) Autonomous norm-acceptance. In: Proceedings of the 5th international workshop on intelligent agents V, agent theories, architectures, and languages, pp 99–112
Conte R, Andrighetto G, Campenni’ M, Paolucci M (2007) Emergent and immergent effects in complex social systems. In: Proceedings of AAAI symposium, social and organizational aspects of intelligence, Washington, DC
Dignum F (1999) Autonomous agents with norms. AI Law 7(1):69–79
Epstein J (2006) Generative social science: studies in agent-based computational modeling. Princeton University Press, Princeton
Fent T (2006) Collective social dynamics and social norms. Munich Personal RePEc Archive
Gintis H, Bowles S, Boyd R, Fehr E (2003) Explaining altruistic behavior in humans. Evol Hum Behav 24(3):153–172
Heckathorn D (1988) Collective sanctions and the compliance norms a formal theory of group-mediated social-control. Am J Soc 94:535–562
Horne C (2007) Explaining norm enforcement. Ration Soc 19(2):139–170
Hume D (1978) Trattato sulla natura umana (trad. it.) Bari, Italy, Laterza
Jones A, Sergot M (1996) A formal characterization of institutionalized power. Logic J Igpl 4(3):429–445
Kelsen H (1991) General theory of norms. Oxford University Press, USA
Lewis DK (1969) Convention: a philosophical study. Harvard University Press, Cambridge
Lindhal L (1977) Position and change: a study in law and logic. In: Springer series: synthese library (originally published in Swedish 1977), vol 112. Reidel, Dordrecht, 318 pp
Lopez y Lopez F, Luck M, d’Inverno M (2002) Constraining autonomy through norms. In: Proceedings of AAMAS ‘02
Myerson RB (1991) Game theory: analysis of conflict. Harvard University Press, Cambridge
Oliver PE (1993) Formal models of collective action. Annu Rev Sociol 19:271–300
Posner R, Rasmusen E (1999) Creating and enforcing norms, with special reference to sanctions. Int Rev Law Econ, pp 369–382
Rosaria C (2009) Rational, goal governed agents: encyclopedia of complexity and systems science. Springer
Savarimuthu B, Purvis M, Cranefield S, Purvis M (2007) Mechanisms for norm emergence in multi-agent societies. Proceedings of 6th joint conference on autonomous agents and multiagent systems (AAMAS), Honolulu, Hawaii (USA)
Sen S, Airiau S (2007) Emergence of norms through social learning. In: Proceedings of the 20 international joint conference on AAAI
Shoham Y, Tennenholtz M (1992) On the synthesis of useful social laws in artificial societies. In: Proceedings of the 10th national conference on artificial intelligence, number 276–282. Kaufmann, San Mateo, California
Shoham Y, Tennenholtz M (1994) Co-learning and the evolution of social activity. Technical Report CS- TR-94-1511, Stanford University
Ullman-Margalit E (1977) The emergence of norms. Clarendon Press, Oxford
van der Torre L, Tan Y (1999) Contrary-to-duty reasoning with preference-based dyadic obligations. Ann Math Artif Intel, pp 1239–1246
von Wright GH (1963) Norm and action: a logical inquiry. Routledge and Kegan Paul, London
Young HP (1998) Individual strategy and social structure: an evolutionary theory of institutions. Princeton University Press, Princeton, NJ
Acknowledgments
This work was supported by the EMIL project (IST-033841), funded by the Future and Emerging Technologies program of the European Commission, in the framework of the initiative Simulating Emergent Properties in Complex Systems.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Campenní, M., Andrighetto, G., Cecconi, F. et al. Normal = Normative? The role of intelligent agents in norm innovation. Mind Soc 8, 153–172 (2009). https://doi.org/10.1007/s11299-009-0063-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11299-009-0063-4