a b s t r a c tThe importance of reputation in human societies is highlighted both by theoretical models and empirical studies. In this paper, we have extended the scope of previous experimental studies based on trust games by creating treatments where players can rate their opponents' behavior and know their past ratings. Our results showed that being rated by other players and letting this rating be known are factors that increase cooperation levels even when rational reputational investment motives are ruled out. More generally, subjects tended to respond to reputational opportunities even when this was neither rational nor explainable by reciprocity.

This paper investigates the relevance of reputation to improve the explorative capabilities of agents in uncertain environments. We have presented a laboratory experiment where sixty-four subjects were asked to take iterated economic investment decisions. An agent-based model based on their behavioural patterns replicated the experiment exactly. Exploring this experimentally grounded model, we studied the effects of various reputational mechanisms on explorative capabilities at a systemic level. The results showed that reputation mechanisms increase the agents' capability for coping with uncertain environments more than individualistic atomistic exploration strategies, although the former does entail a certain amount of false information inside the system.

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This paper presents the results of laboratory experiments on the relevance of reputation for trust and cooperation in social interaction. We have extended a repeated investment game by adding new treatments where reputation is taken more explicitly into account than before. We then compared treatments where the investor and the trustee rate each other and treatments where the investor and the trustee were rated by a third party. The results showed that: (i) third party reputation positively affects cooperation by encapsulating trust; (ii) certain differences in the reputation mechanism can generate different cooperation outcomes. These results have interesting implications for the recent sociological debate on the normative pillars of markets.

The paper aims at presenting an agent-based modeling exercise to illustrate how small differences in the cognitive properties of agents can generate very different macro social properties. We argue that it is not necessary to assume highly complicated cognitive architectures to introduce cognitive properties that matter for computational social science purposes. Our model is based on different simulation settings characterized by a gradual sophistication of behavior of agents, from simple heuristics to macro-micro feedback and other second-order properties. Agents are localized in a spatial interaction context. They have an individual task but are influenced by a collective coordination problem. The simulation results show that agents can generate efficiency at a macro level particularly when socio-cognitive sophistication of their behavior increases.

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The paper aims to describe an agent-based prototype that has been created to investigate the relation among local labour markets, entrepreneurship and human capital in IDs. It basically describes the building blocks of the prototype, the agents acting in it and the forces that drive its most interesting dynamics. Some interesting hypotheses to investigate are sketched, too.