Modelling the Social Contract: An agent-based Model of Hobbes' Contract Theory

The aim of this paper is to build a computational model that presents the effects of social dynamics such as evolution on populations applying the theory of Hobbesian Social Contract, social learning and norm diffusion. The phenomenon we are studying is the so-called tragedy of the commons, in which individual agents, having open access to a resource unconstrained by common social structures, act according to their own self-interest, seeking to maximise their own profits. Developing the theoretical framework and agent-based model, we applied to our artificial environment the norm associated with altruism, which modifies agents' behaviour during the simulation, which in turn affects the distribution of wealth. Through the behavioural space, we show that under certain circumstances specified in the parameter, it is possible to obtain a social contract and, as a result, a state of equilibrium. We show that individuals who have obtained the norm are able to enter into a contract, resulting in a rising wealth of the population and a more equilibrium distribution, while if they do not, more inequalities emerge. However, our model is a simplification of Hobbes' theory, admittedly, our agents can spontaneously establish cooperation but there are no complex structures, such as psychological ones, or moral cognition. We believe that this is a skeletal description of the Hobbesian social contract, in which self-interested individuals without obligation to cooperate agree to abide by a norm and its benefits. Depending on how profitable cooperation is (due to the redistribution) and the number of altruistic agents, the community members work for the common good

Reti complesse e resistenze ai guasti

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R&D Subsidization effect and network centralization. Evidence from an agent-based micro-policy simulation

This paper presents an agent-based micro-policy simulation model assessing public R&D policy effect when R&D and non-R&D performing companies are located within a network. We set out by illustrating the behavioural structure and the computational logic of the proposed model; then, we provide a simulation experiment where the pattern of the total level of R&D activated by a fixed amount of public support is analysed as function of companies’ network topology. More specifically, the suggested simulation experiment shows that a larger “hubness” of the network is more likely accompanied with a decreasing median of the aggregated total R&D performance of the system. Since the aggregated firm idiosyncratic R&D (i.e., the part of total R&D independent of spillovers) is slightly increasing, we conclude that positive cross-firm spillover effects - in the presence of a given amount of support - have a sizeable impact within less centralized networks, where fewer hubs emerge. This may question the common wisdom suggesting that larger R&D externality effects should be more likely to arise when few central champions receive a support

La diffusione di tratti culturali tra reti di agenti artificiali

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A neural network model for explaining the asymmetries between linguistic production and linguistic comprehension

Several kinds of empirical evidence point to the existence of an asymmetry between linguistic production and linguistic comprehension: in general, understanding words seems to be easier than producing them. In this contribution we propose a neural model of the relationships between the semantic and the lexical systems. Our model explains the asymmetry between language comprehension and production as an effect of the difference between the dimensions of the brain areas which process semantic and lexical information. In fact, the model\u27s performance in lexical recall is worse than the performance in semantic recall due to the fact that the semantic network is constituted of more computational units (neurons) then the lexical network

How Social Norms Can Make the World More Regular and Better

Is there any difference between social norms and mere regularities emerging spontaneously from the behaviours of entities that have no norm-based cognition? And if so, which effects do we expect to observe in a world in which agents are endowed with such a type of cognition? The agent-based simulations presented here are aimed to understand what would happen in a world populated by normative agents, able to recognize norms and to reason upon them, compared to other, cognitively, less complex agents, following only their own individual goals

Interacting networks as models of cultural change

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What Do Agent-Based and Equation-Based Modelling Tell Us About Social Conventions: The Clash Between ABM and EBM in a Congestion Game Framework

In this work simulation-based and analytical results on the emergence steady states in traffic-like interactions are presented and discussed. The objective of the paper is twofold: i) investigating the role of social conventions in coordination problem situations, and more specifically in congestion games; ii) comparing simulation-based and analytical results to figure out what these methodologies can tell us on the subject matter. Our main issue is that Agent-Based Modelling (ABM) and the Equation-Based Modelling (EBM) are not alternative, but in some circumstances complementary, and suggest some features distinguishing these two ways of modeling that go beyond the practical considerations provided by Parunak H.V.D., Robert Savit and Rick L. Riolo. Our model is based on the interaction of strategies of heterogeneous agents who have to cross a junction. In each junction there are only four inputs, each of which is passable only in the direction of the intersection and can be occupied only by an agent one at a time. The results generated by ABM simulations provide structured data for developing the analytical model through which generalizing the simulation results and make predictions. ABM simulations are artifacts that generate empirical data on the basis of the variables, properties, local rules and critical factors the modeler decides to implement into the model; in this way simulations allow generating controlled data, useful to test the theory and reduce the complexity, while EBM allows to close them, making thus possible to falsify them.Agent-Based Modelling, Equation-Based Modelling, Congestion Game, Model of Social Phenomena

Comparison of voter and Glauber ordering dynamics on networks

We study numerically the ordering process of two very simple dynamical models for a two-state variable on several topologies with increasing levels of heterogeneity in the degree distribution. We find that the zero-temperature Glauber dynamics for the Ising model may get trapped in sets of partially ordered metastable states even for finite system size, and this becomes more probable as the size increases. Voter dynamics instead always converges to full order on finite networks, even if this does not occur via coherent growth of domains. The time needed for order to be reached diverges with the system size. In both cases the ordering process is rather insensitive to the variation of the degreee distribution from sharply peaked to scale-free.Comment: 12 pages, 12 figure