Marco Campennì

Internalizing Norms: A Cognitive Model of Social Norms' Internalization

Internalization is at study in social-behavioural sciences and moral philosophy; lately, the debate was revamped within the rationality approach to the study of cooperation and compliance because internalization is a less costly and more reliable enforcement system than social control. But how does it work? So far, poor attention was paid to mental underpinnings of internalization. This article advocates a rich cognitive model of different types, degrees and factors of internalization. In future work, it will be implemented on a normative agent platform to simulate the individual and social effect of internalization.

PSO (Particle Swarm Optimization): One Method, Many Possible Applications

Particle Swarm Optimization (PSO ) is an optimization technique, deriving from the EO [5]: the main features are the natural inspiration and the possibility to implement PSO onto different levels. This chapter is divided in three section: (1) the PSO definitions and relationship with MAS (Multi Agent Systems) framework; (2) three applications of PSO methods; (3) some general conclusions and perspectives. We try to show that PSO has a marked multidisciplinary character since systems with swarm characteristics can be observed in a variety of domains: the main argument in favor to PSO is proper the multidisciplinary character. Besides, POS can resolve multiobjective otpimization problems in efficient way, because POS naturally incorporates some concepts from Pareto-Optimal framework.

Norm and Social Compliance: A Computational Study

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.

Quasi-PSO Algorithm for Modeling Foraging Dynamics in Social Mammals

In this paper, the authors present a computational model of a fundamental social phenomenon in the study of animal behavior: the foraging. The purpose of this work is, first, to test the validity of the proposed model compared to another existing model, the flocking model; then, to try to understand whether the model may provide useful suggestions in studying the size of the group in some species of social mammals.