Abstract
We describe a general tool for solving belief revision problems with a range of different operators. Our tool allows a user to flexibly specify a total pre-order over states, using simple selection boxes in a graphic user interface. In this manner, we are able to calculate the result of any AGM revision operator. The user is also able to specify so-called trust partitions to calculate the result of trust-sensitive revision. The overall goal is to provide users with a simple tool that can be used in applications involving AGM-style revision. While the tool can be demonstrated and tested as a standalone application with a fixed user interface, what we have actually developed is a set of libraries and functions that can flexibly be incorporprated in other systems. It is anticipated that this tool will be useful for experimentation, education, and prototyping to solve problems in formal reasoning.
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Notes
- 1.
Technical documentation and download available at http://kotlinlang.org.
References
Alchourrón, C.E., Gärdenfors, P., Makinson, D.: On the logic of theory change: partial meet functions for contraction and revision. J. Symbolic Logic 50(2), 510–530 (1985)
Dalal, M.: Investigations into a theory of knowledge base revision. In: Proceedings of the National Conference on Artificial Intelligence (AAAI), pp. 475–479 (1988)
Delgrande, J.P., Liu, D.H., Schaub, T., Thiele, S.: COBA 2.0: a consistency-based belief change system. In: Mellouli, K. (ed.) ECSQARU 2007. LNCS (LNAI), vol. 4724, pp. 78–90. Springer, Heidelberg (2007). doi:10.1007/978-3-540-75256-1_10
Eiter, T., Gottlob, G.: On the complexity of propositional knowledge base revision, updates and counterfactuals. Artif. Intell. 57(2–3), 227–270 (1992)
Fermé, E., Hansson, S.O.: Selective revision. Stud. Logica. 63(3), 331–342 (1999)
Hunter, A., Booth, R.: Trust-sensitive belief revision. In: International Joint Conference on Artificial Intelligence (IJCAI), pp. 3062–3068 (2015)
Hunter, A., Schwarzentruber, F.: Arbitrary announcements in propositional belief revision. In: Proceedings of the Workshop on Declarative and Ampliative Reasoning (DARE) (2015)
Katsuno, H., Mendelzon, A.O.: Propositional knowledge base revision and minimal change. Artif. Intell. 52(2), 263–294 (1992)
Liberatore, P.: Revision by history. J. Artif. Intell. Res. 52, 287–329 (2015)
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Hunter, A., Tsang, E. (2016). GenB: A General Solver for AGM Revision. In: Michael, L., Kakas, A. (eds) Logics in Artificial Intelligence. JELIA 2016. Lecture Notes in Computer Science(), vol 10021. Springer, Cham. https://doi.org/10.1007/978-3-319-48758-8_40
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DOI: https://doi.org/10.1007/978-3-319-48758-8_40
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