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相关论文: A flexible framework for defeasible logics

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We extend answer set semantics to deal with inconsistent programs (containing classical negation), by finding a ``best'' answer set. Within the context of inconsistent programs, it is natural to have a partial order on rules, representing a…

计算机科学中的逻辑 · 计算机科学 2007-05-23 Davy Van Nieuwenborgh , Dirk Vermeir

Logical frameworks provide natural and direct ways of specifying and reasoning within deductive systems. The logical framework LF and subsequent developments focus on finitary proof systems, making the formalization of circular proof…

计算机科学中的逻辑 · 计算机科学 2023-05-11 Zhibo Chen , Frank Pfenning

We present a logical framework that enables us to define a formal theory of computational trust in which this notion is analysed in terms of epistemic attitudes towards the possible objects of trust and in relation to existing evidence in…

计算机科学中的逻辑 · 计算机科学 2025-06-19 Francesco A. Genco

Extensive research on formal verification of machine learning (ML) systems indicates that learning from data alone often fails to capture underlying background knowledge. A variety of verifiers have been developed to ensure that a…

计算机科学中的逻辑 · 计算机科学 2023-11-17 Thomas Flinkow , Barak A. Pearlmutter , Rosemary Monahan

We present modeling for conceptual combinations which uses the mathematical formalism of quantum theory. Our model faithfully describes a large amount of experimental data collected by different scholars on concept conjunctions and…

人工智能 · 计算机科学 2015-12-31 Diederik Aerts , Sandro Sozzo

An algorithm for computing the stable model semantics of logic programs is developed. It is shown that one can extend the semantics and the algorithm to handle new and more expressive types of rules. Emphasis is placed on the use of…

计算机科学中的逻辑 · 计算机科学 2007-05-23 Patrik Simons

This paper presents and discusses several methods for reasoning from inconsistent knowledge bases. A so-called argumentative-consequence relation taking into account the existence of consistent arguments in favor of a conclusion and the…

人工智能 · 计算机科学 2013-03-08 Salem Benferhat , Didier Dubois , Henri Prade

We revisit evaluation of logical formulas that allow both uninterpreted relations, constrained to be finite, as well as an interpreted vocabulary over an infinite domain. This formalism was denoted embedded finite model theory in the past.…

计算机科学中的逻辑 · 计算机科学 2024-05-22 Michael Benedikt , Ehud Hrushovski

Substantial efforts have been made in developing various Decision Modeling formalisms, both from industry and academia. A challenging problem is that of expressing decision knowledge in the context of incomplete knowledge. In such contexts,…

人工智能 · 计算机科学 2023-12-19 Đorđe Marković , Simon Vandevelde , Linde Vanbesien , Joost Vennekens , Marc Denecker

In the present paper, the existence and multiplicity problems of extensions are addressed. The focus is on extension of the stable type. The main result of the paper is an elegant characterization of the existence and multiplicity of…

人工智能 · 计算机科学 2007-05-23 Bart Verheij

This thesis concerns the development of a framework that facilitates the design and analysis of formal systems. Specifically, this framework provides a specification language which supports the concise and direct description of formal…

计算机科学中的逻辑 · 计算机科学 2009-10-06 Andrew Gacek

Mechanistic Interpretability (MI) aims to understand neural networks through causal explanations. Though MI has many explanation-generating methods, progress has been limited by the lack of a universal approach to evaluating explanations.…

机器学习 · 计算机科学 2025-05-05 Kola Ayonrinde , Louis Jaburi

We present a comprehensive programme analysing the decomposition of proof systems for non-classical logics into proof systems for other logics, especially classical logic, using an algebra of constraints. That is, one recovers a proof…

计算机科学中的逻辑 · 计算机科学 2023-10-20 Alexander V. Gheorghiu , David J. Pym

We present a logical framework to represent and reason about stochastic optimization problems based on probability answer set programming. This is established by allowing probability optimization aggregates, e.g., minimum and maximum in the…

人工智能 · 计算机科学 2013-04-15 Emad Saad

Possibilistic logic offers a qualitative framework for representing pieces of information associated with levels of uncertainty of priority. The fusion of multiple sources information is discussed in this setting. Different classes of…

人工智能 · 计算机科学 2013-01-18 Salem Benferhat , Didier Dubois , Souhila Kaci , Henri Prade

In this paper, we propose a comprehensive benchmark to investigate models' logical reasoning capabilities in complex real-life scenarios. Current explanation datasets often employ synthetic data with simple reasoning structures. Therefore,…

人工智能 · 计算机科学 2022-10-25 Yinya Huang , Hongming Zhang , Ruixin Hong , Xiaodan Liang , Changshui Zhang , Dong Yu

The programming language Prolog makes declarative programming possible, at least to a substantial extent. Programs may be written and reasoned about in terms of their declarative semantics. All the advantages of declarative programming are…

计算机科学中的逻辑 · 计算机科学 2023-08-31 Włodzimierz Drabent

We identify the (filter representation of the) logic behind the recent theory of coherent sets of desirable (sets of) things, which generalise coherent sets of desirable (sets of) gambles as well as coherent choice functions, and show that…

逻辑 · 数学 2024-06-21 Gert de Cooman , Arthur Van Camp , Jasper De Bock

The satisfiability problem of hybrid logics with the downarrow binder is known to be undecidable. This initiated a research program on decidable and tractable fragments. In this paper, we investigate the effect of restricting the…

计算机科学中的逻辑 · 计算机科学 2015-03-13 Arne Meier , Martin Mundhenk , Thomas Schneider , Michael Thomas , Volker Weber , Felix Weiss

To build intelligent machine learning systems, there are two broad approaches. One approach is to build inherently interpretable models, as endeavored by the growing field of causal representation learning. The other approach is to build…

机器学习 · 计算机科学 2024-12-10 Goutham Rajendran , Simon Buchholz , Bryon Aragam , Bernhard Schölkopf , Pradeep Ravikumar