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  1. Modeling of Phenomena and Dynamic Logic of Phenomena.Boris Kovalerchuk, Leonid Perlovsky & Gregory Wheeler - 2011 - Journal of Applied Non-Classical Logic 22 (1):1-82.
    Modeling a complex phenomena such as the mind presents tremendous computational complexity challenges. Modeling field theory (MFT) addresses these challenges in a non-traditional way. The main idea behind MFT is to match levels of uncertainty of the model (also, a problem or some theory) with levels of uncertainty of the evaluation criterion used to identify that model. When a model becomes more certain, then the evaluation criterion is adjusted dynamically to match that change to the model. This process is called (...)
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  • Two Adaptive Logics of Norm-Propositions.Mathieu Beirlaen & Christian Straßer - 2013 - Journal of Applied Logic 11 (2):147-168.
    We present two defeasible logics of norm-propositions (statements about norms) that (i) consistently allow for the possibility of normative gaps and normative conflicts, and (ii) map each premise set to a sufficiently rich consequence set. In order to meet (i), we define the logic LNP, a conflict- and gap-tolerant logic of norm-propositions capable of formalizing both normative conflicts and normative gaps within the object language. Next, we strengthen LNP within the adaptive logic framework for non-monotonic reasoning in order to meet (...)
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  • Modelling Phenomena and Dynamic Logic of Phenomena.Boris Kovalerchuk, Leonid Perlovsky & Gregory Wheeler - 2012 - Journal of Applied Non-Classical Logics 22 (1-2):53-82.
    Modelling a complex phenomenon such as the mind presents tremendous computational complexity challenges. Modelling field theory addresses these challenges in a non-traditional way. The main idea behind MFT is to match levels of uncertainty of the model with levels of uncertainty of the evaluation criterion used to identify that model. When a model becomes more certain, then the evaluation criterion is adjusted dynamically to match that change to the model. This process is called the Dynamic Logic of Phenomena for model (...)
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  • An Axiomatic Characterization of Temporalised Belief Revision in the Law.Luciano H. Tamargo, Diego C. Martinez, Antonino Rotolo & Guido Governatori - forthcoming - Artificial Intelligence and Law:1-21.
    This paper presents a belief revision operator that considers time intervals for modelling norm change in the law. This approach relates techniques from belief revision formalisms and time intervals with temporalised rules for legal systems. Our goal is to formalise a temporalised belief base and corresponding timed derivation, together with a proper revision operator. This operator may remove rules when needed or adapt intervals of time when contradictory norms are added in the system. For the operator, both constructive definition and (...)
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