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  • Sequence Semantics for Normative Agents

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    Governatori161544-Accepted.pdf (322.2Kb)
    File version
    Accepted Manuscript (AM)
    Author(s)
    Governatori, Guido
    Olivieri, Francesco
    Calardo, Erica
    Rotolo, Antonino
    Cristani, Matteo
    Griffith University Author(s)
    Olivieri, Francesco
    Year published
    2016
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    Abstract
    We proposed a novel framework for the representation of goals and other mental-like attitudes in terms of degree of expected outcomes, where an outcome is an order of possible alternatives. The sequences of alternatives is modelled by a non-classical (substructural) operator. In this paper we provide a modal logic based axiomatisation of the intuition they propose, and we discuss some variants (in particular for the notion of social intention, intentions that are compliant with norms). Given that the outcome operator is substructural, we first propose a novel sequence semantics (a generalisation of possible world semantics) ...
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    We proposed a novel framework for the representation of goals and other mental-like attitudes in terms of degree of expected outcomes, where an outcome is an order of possible alternatives. The sequences of alternatives is modelled by a non-classical (substructural) operator. In this paper we provide a modal logic based axiomatisation of the intuition they propose, and we discuss some variants (in particular for the notion of social intention, intentions that are compliant with norms). Given that the outcome operator is substructural, we first propose a novel sequence semantics (a generalisation of possible world semantics) to model the outcome operator, and we prove that the axiomatisation is sound and complete with respect to the new semantics.
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    Conference Title
    Lecture Notes in Computer Science
    Volume
    9862
    DOI
    https://doi.org/10.1007/978-3-319-44832-9_14
    Copyright Statement
    © Springer International Publishing Switzerland 2016. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher.The original publication is available at www.springerlink.com
    Subject
    Artificial intelligence
    Science & Technology
    Computer Science, Information Systems
    Computer Science, Theory & Methods
    Publication URI
    http://hdl.handle.net/10072/411948
    Collection
    • Conference outputs

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