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This article is inspired by Joshua Epstein's generativist paradigm, according to which to possibility of explaining a phenomenon and of influencing its process of existence depend on the availability of instruments that can artificially reproduce it, or in other words simulate its «generation». «Agent based simulation » possesses the requirements that enable the development of a similar cognitive program. The essay describes this instrument's characteristics, from the modeling to the cellular automaton used in biology, of which the «agent based simulation» in an exemplary heir. The second part of the article focuses on applications of generative simulation, with reference to the interpretation of interdependant dynamics in complex situations as useful resources for sociological analysis of micro and macro phenomena.

An exploration of the implications of developments in artificial intelligence for social scientific research, which builds on the theoretical and methodological insights provided by "Simulating societies".; This book is intended for worldwide library market for social science subjects such as sociology, political science, geography, archaeology/anthropology, and significant appeal within computer science, particularly artificial intelligence. Also personal reference for researchers.

Abstract. In the last few years, the study of social phenomena has hosted a renewal of interest in Computational Social Science (CSS). While this field is not new – Axelrod's first computational work on the evolution of cooperation goes back to 1981 – CSS has recently resurged under the pressure of quantitative social science and the application of Big Data analytics to social datasets. However, Big Data is no panacea and the data deluge that it provides raises more questions than it answers. The aim of this paper is to present an overview in which CSS will be introduced and the costs of CSS will be balanced against its benefits, in an attempt to propose an integrative view of the new and the old practice of CSS. In particular, two routes to integration will be drawn. First, it will be advocated that social data mining and computational modeling need to be integrated. Second, we will introduce the generative approach, aimed to understand how social phenomena can be generated starting from the micro-components, including psychological mechanisms, and we will discuss the necessity of combining it with the anticipatory, data-driven objective. By these means, Computational Social Science will develop into a more comprehensive field of Computational Social and Behavioral Science in which data science, ICT, as well as the behavioral and social sciences will be fruitfully integrated.

Book Cover; Book Title; Title; Copyright; Contents; Preface; Notes on contributors; Chapter 1 Introduction ; Part I The simulation of social theories ; Chapter 2 A model of the emergence of new political actors ; Chapter 3 Division of labour and social co-ordination modes: a simple simulation model ; Chapter 4 Emergence of kinship structures: a multi-agent approach ; Chapter 5 Cities can be agents too: a model for the evolution of settlement systems ; Chapter 6 The EOS project: integrating two models of Palaeolithic social change.

Introduction /Rosaria Conte, Giulia Andrighetto, and Marco Campennì --Loops in Social Dynamics /Giulia Andrighetto and Rosaria Conte --Agent-Based Social Simulation and Its Necessity for Understanding Socially Embedded Phenomena /Bruce Edmonds --How Are Norms Brought About? : A State of the Art of Current Research /Martin Neumann --Modeling Hume's Theory of Norm Emergence /Oliver Will and Rainer Hegselmann --Norms' Dynamics as a Complex Loop /Giulia Andrighetto and Rosaria Conte --Hunting for Norms in Unpredictable Societies /Marco Campennì [and others] --The Derivation of EMIL-S from EMIL-A /Ulf Lotzmann, Michael Möhring, and Klaus G. Troitzsch --Demonstrating the Theory /Maria Xenitidou [and others] --The Role of Norm Internalizers in Mixed Populations /Giulia Andrighetto, Daniel Villatoro, and Rosaria Conte --Summary and Conclusions /Rosaria Conte, Giulia Andrighetto, and Marco Campennì.

This paper presents an Agent-Based Model aimed to reproduce the demographics, economic and employment variables of a Southern Italian region (Campania) where one specific variant of Extortion Racketeering Systems (Erss), camorra, is highly active and prosperous. Preliminary results of a set of simulations show the effects of varying levels of extortion and punishment on the rates of inactivity, employment, etc. of a population of agents endowed with social learning mechanisms