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Norm and Social Compliance: A Computational Study

Volume 2, Issue 1. Copyright © 2010. 13 pages.
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DOI: 10.4018/jats.2010120104
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MLA

Campennì, Marco, Federico Cecconi, Giulia Andrighetto and Rosaria Conte. "Norm and Social Compliance: A Computational Study." IJATS 2.1 (2010): 50-62. Web. 20 Oct. 2014. doi:10.4018/jats.2010120104

APA

Campennì, M., Cecconi, F., Andrighetto, G., & Conte, R. (2010). Norm and Social Compliance: A Computational Study. International Journal of Agent Technologies and Systems (IJATS), 2(1), 50-62. doi:10.4018/jats.2010120104

Chicago

Campennì, Marco, Federico Cecconi, Giulia Andrighetto and Rosaria Conte. "Norm and Social Compliance: A Computational Study," International Journal of Agent Technologies and Systems (IJATS) 2 (2010): 1, accessed (October 20, 2014), doi:10.4018/jats.2010120104

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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 article, 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. After a brief presentation of a normative agent architecture, the preliminary results of agent-based simulations testing the impact of norm recognition and the role of normative beliefs in the emergence and stabilization of social norms are presented and discussed. We focused our attention on the effects which the use of a cognitive architecture (namely a norm recognition module) produces on the environment.
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1 Introduction

Traditionally, the scientific domain of normative agent systems presents two main directions of research. The first, related to Normative Multia- gent Systems, focuses on intelligent agent architecture, and in particular on normative agents and their capacity to decide on the grounds of norms and the associated incentive or sanction (see Boella et al., 2006). This scientific area absorbed the results obtained in the formalization of normative concepts, from deontic-logic (von Wright, 1963; Alchourròn & Bulygin, 1971), to the theory of normative position (Lindhal, 1977), to the dynamics of normative systems (Alchourròn et al., 1985). Those studies have provided Normative Multiagent Systems with a formal analysis of norms, thus giving crucial insights to represent and reason upon norms.

The second is focused on much simpler agents and on the emergence of regularities from agent societies. Very often, the social scientific study of norms goes back to the philosophical tradition that defines norms as regularities emerging from reciprocal expectations (Lewis, 1969; Bicchieri, 2006; Epstein, 2006). Indeed, interesting sociological works (Oliver, 1993) point to norms as public goods, the provision of which is promoted by 2nd- order cooperation (Heckathorn, 1988; Horne, 2007). This view inspired most recent work of evolutionary game-theorists (Gintis et al., 2003), who explored the effect of punishers or strong reciprocators on the group’s fitness, but did not account for the individual decision to follow a norm.

While the latter approach has been mainly interested in how social norms emerge, spread and change over time, the Normative Multiagent Sistem approach has focused on the question why agents comply with norms and how is it possible that norms operate upon autonomous intelligent agents. No apparent contamination and integration between these different directions of investigation has been achieved so far. In particular, it is unclear how something more than regularities can emerge in a population of intelligent autonomous agents and whether agents’ mental capacities play any relevant role in the emergence of norm (see section Existent Approaches).

The aim of this paper is help clarify what aspects of cognition are essential for norm emergence and norm innovation. We will concentrate on one of these aspects, i.e. norm recognition. We will simulate agents endowed with the capacity to tell what a norm is, while observing their social environment.

One might question why start with norm recognition. After all, isn’t it more important to understand why agents observe norms? Probably, it is. However, whereas this question has been answered to some extent (Conte & Castelfranchi, 1995, 1999) the question how agents tell norms has received poor attention so far.

In this paper, we will address the antecedent phenomenon, norm recognition, postponing the consequent, norm compliance, to future studies. In particular, we will endeavour to show the impact of norm recognition on the emergence of a norm. More precisely, we will observe agents endowed with the capacity to recognize a norm (or a behavior based on a norm), to generate new normative beliefs and to transmit them to other agents by communicative acts or direct behaviors.

We intend to show whether a society of such normative agents allows social norms to emerge. The notion of norms that we refer to (Conte and Castelfranchi, 2006) is rather general. Unlike a moral notion, which is based on the sense of right or wrong, norms are here meant in the broadest sense, as behaviors spreading to the extent that and because (a) they are prescribed by one agent to another, (b) and the corresponding normative beliefs spread among these agents.

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