263 research outputs found

    On ‘common-sense ontology’:A comment on the paper by Frank Hindriks and Francesco Guala

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    This note comments on Hindriks and Guala’s ‘unified theory of institutions’. One of the components that Hindriks and Guala seek to unify, and which they claim is unsatisfactory on its own, is the analysis of conventions that derives from the work of Lewis. I argue that the Lewisian approach provides simple and powerful explanations of many regularities in the social behaviour of humans and other animals. Those explanations can be seen as good social science even if, as Hindriks and Guala argue, they do not fit with common-sense ontology

    Solidarity in Consumption

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    Contrary to a common picture of relationships in a market economy, people often express communal and membership-seeking impulses via consumption choices, purchasing goods and services because other people are doing so as well. Shared identities are maintained and created in this way. Solidarity goods are goods whose value increases as the number of people enjoying them increases. Exclusivity goods are goods whose value decreases as the number of people enjoying them increases. Distinctions can be drawn among diverse value functions, capturing diverse relationships between the value of goods and the value of shared or unshared consumption. Though markets spontaneously produce solidarity goods, individuals sometimes have difficulty in producing such goods on their own, or in coordinating on choosing them. Here law has a potential role. There are implications for trend setting, clubs, partnerships, national events, social cascades, and compliance without enforcement

    What am I allowed to do here?: Online Learning of Context-Specific Norms by Pepper

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    Social norms support coordination and cooperation in society. With social robots becoming increasingly involved in our society, they also need to follow the social norms of the society. This paper presents a computational framework for learning contexts and the social norms present in a context in an online manner on a robot. The paper utilizes a recent state-of-the-art approach for incremental learning and adapts it for online learning of scenes (contexts). The paper further utilizes Dempster-Schafer theory to model context-specific norms. After learning the scenes (contexts), we use active learning to learn related norms. We test our approach on the Pepper robot by taking it through different scene locations. Our results show that Pepper can learn different scenes and related norms simply by communicating with a human partner in an online manner.Comment: The final authenticated publication is available online at https://doi.org/10.1007/978-3-030-62056-1_1

    Networks and Mechanisms of Interdependence: Theoretical Developments Beyond the Rational Action Model

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    There is interdependence when the actions of an individual influence the decisions (and later actions) of other individuals. This paper claims that social networks define the structure of that range of influence and unleash a number of mechanisms that go beyond those captured by rational action theory. Networks give access to the ideas and actions of other individuals, and this exposure determines the activation of thresholds, the timing of actions, and the emergence of contagion processes, informational cascades and epidemics. This paper sustains that rational action theory does not offer the necessary tools to model these processes if it is not inserted in a general theory of networks. This is especially the case in the context opened by new information and communication technologies, where the interdependence of individuals is acquiring greater empirical relevance
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