Gennaro Di Tosto

A model for simulating reputation dynamics in industrial districts

Abstract In this work we try to draw an interdisciplinary framework aimed to integrate a socio-cognitive approach with organizational research about industrial clusters, in order to investigate whether and how social evaluations may affect clusters’ dynamics. Industrial districts are sort of “small-worlds” that provide a suitable environment for testing the predictions of our model through multi-agent-based social simulation (MABSS) experiments. Artificial agents will be allowed to exchange products and to transmit social evaluations, and the main features of a cluster will be implemented. The effects of evaluation transmission on products’ quality, partner selection and cheaters’ isolation will be discussed.

No smoking here: values, norms and culture in multi-agent systems

We use the example of the introduction of the anti-smoking legislation to model the relationship between the cultural make-up, in terms of values, of societies and the acceptance of and compliance with norms. We present two agent-based simulations and discuss the challenge of modeling sanctions and their relation to values and culture.

A Model of Social Organization and the Evolution of Food Sharing in Vampire Bats

This article is aimed at exploring the role of groups in the evolution of a well-known form of altruism: blood sharing among vampire bats. In particular, we are interested in the formation and maintenance of new social structures (roosts) from initial populations as a consequence of both demographic growth and social organization. The example of vampire bats is especially interesting because of the flexible roost-switching behavior shown by these animals in nature. The main hypothesis made in this article concerns the role of grooming networks in roost formation, and was investigated by means of simula tion grounded on ethological evidence. The use of simulation allows the discussion of generative hypotheses on the origin of roosts, which are emergent from individual behavior. Besides confirming the main expectations, the results point to the need for a natural ordering in grooming partner selection. This ordering can be obtained not only through kin-based groups but also through the maintenance of a non kin-based precedence rule.

Simulation and NorMAS

In this chapter, we discuss state of the art and future perspective of the study of norms with simulative methodologies, in particular employing agent-based simulation. After presenting the state of the art and framing the simulative research on norms in a norm life-cycle schema, we list those research challenges that we feel more apt to be tackled by the simulative approach. We conclude the chapter with the indications for the realization of a NorMAS simulation platform, illustrated by selected scenarios.

Reputation and Economic Performance in Industrial Districts: Modelling Social Complexity Through Multi-Agent Systems

Industrial districts (Ids) can be conceived as complex systems made of heterogeneous but strictly interrelated and complementary firms that interact in a non-linear way. One of the distinctive features of industrial districts is the tight connection existing between the social community and the firms: in this context, economic exchanges are mainly informed by social relationships and holding good reputation is an asset that may actually foster potential relations. In this work we model the effects of social evaluations on firms in an arepsicial cluster through Multi-Agent Simulation (MAS) techniques, in order to investigate whether and how different kinds of social evaluations have an impact on firms’ quality and on their profits. Likewise, we compare the effects of sincere and insincere information on the economic performances of the single firms and of the cluster as a whole.

Multi-Agent-Based Simulation X

Urban and Environmental Modelling.- Cumulative Effects and Emergent Properties of Multiple-Use Natural Resources.- Micro-scale Simulation of the Macro Urban Form: Opportunities for Exploring Urban Change and Adaptation.- Simulation of Economic Behaviour.- An Agent-Based Framework for Assessing the Cost of Committal Search in Supply Networks.- Does Cognitive Capacity Matter When Learning Using Genetic Programming in Double Auction Markets?.- A Multi-Agent System for Adaptive Production Networks.- Methods and Methodologies.- A Multi-environment Multi-agent Simulation Framework for Self-organizing Systems.- Software Development Process Simulation: Multi Agent-Based Simulation versus System Dynamics.- Agent-Based Simulations with Beliefs and SPARQL-Based Ask-Reply Communication.- Stigmergic Modeling of Hierarchical Task Networks.- Modelling of Social Phenomena.- The Impact of Naive Agents in Heterogeneous Trust-Aware Societies.- HUME1.0 - An Agent-Based Model on the Evolution of Trust in Strangers and Division of Labour.- Mentat: A Data-Driven Agent-Based Simulation of Social Values Evolution.

Simulating Social Behaviour Implementing Agents Endowed with Values and Drives

We present a working model of agent’s social behaviour based on drives and values. Drives represent internal needs of the agents; values are used to prioritise them. Discussed in the context of a simulation scenario centred around smoking behaviour in public places, the designed system proves itself useful to tackle issues where agents face conflicting decision’s choices, or where agent’s behaviour has negative side-effects for other agents.

Vampire Bats & The Micro-Macro Link

An evolutionary variant of the Micro-Macro Link (MML) theory is proposed. According to the MML theory, behaviour at the individual level generates higher level structures (bottom-up process), which feed back to the lower level (topdown), reinforcing the producing behaviour either directly or indirectly, i.e. acting on the mind of the agent. Focusing on the evolution of pro-social behaviour, we explore these two types of link by means of simulation experiments. The experiments were aimed at studying the role of groups in the performances of populations of agents exchanging helping behaviour (simple loop) and the role of cognitive mediators (i.e. goals) and social norms in the spreading of altruism, described as a purposeful action (complex loop).