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Hauptverfasser: de Lima, Tiago, Lorini, Emiliano, Perrotin, Elise, Schwarzentruber, François
Format: Preprint
Veröffentlicht: 2024
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Online-Zugang:https://arxiv.org/abs/2412.14073
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author de Lima, Tiago
Lorini, Emiliano
Perrotin, Elise
Schwarzentruber, François
author_facet de Lima, Tiago
Lorini, Emiliano
Perrotin, Elise
Schwarzentruber, François
contents We introduce a novel language for reasoning about agents' cognitive attitudes of both epistemic and motivational type. We interpret it by means of a computationally grounded semantics using belief bases. Our language includes five types of modal operators for implicit belief, complete attraction, complete repulsion, realistic attraction and realistic repulsion. We give an axiomatization and show that our operators are not mutually expressible and that they can be combined to represent a large variety of psychological concepts including ambivalence, indifference, being motivated, being demotivated and preference. We present a dynamic extension of the language that supports reasoning about the effects of belief change operations. Finally, we provide a succinct formulation of model checking for our languages and a PSPACE model checking algorithm relying on a reduction into TQBF. We present some experimental results for the implemented algorithm on computation time in a concrete example.
format Preprint
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institution arXiv
publishDate 2024
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spellingShingle A Computationally Grounded Framework for Cognitive Attitudes (extended version)
de Lima, Tiago
Lorini, Emiliano
Perrotin, Elise
Schwarzentruber, François
Logic in Computer Science
Artificial Intelligence
We introduce a novel language for reasoning about agents' cognitive attitudes of both epistemic and motivational type. We interpret it by means of a computationally grounded semantics using belief bases. Our language includes five types of modal operators for implicit belief, complete attraction, complete repulsion, realistic attraction and realistic repulsion. We give an axiomatization and show that our operators are not mutually expressible and that they can be combined to represent a large variety of psychological concepts including ambivalence, indifference, being motivated, being demotivated and preference. We present a dynamic extension of the language that supports reasoning about the effects of belief change operations. Finally, we provide a succinct formulation of model checking for our languages and a PSPACE model checking algorithm relying on a reduction into TQBF. We present some experimental results for the implemented algorithm on computation time in a concrete example.
title A Computationally Grounded Framework for Cognitive Attitudes (extended version)
topic Logic in Computer Science
Artificial Intelligence
url https://arxiv.org/abs/2412.14073