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Related papers: Non-Monotonicity in Probabilistic Reasoning

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The aim of this article is to promote the use of probabilistic methods in the study of problems in mathematical general relativity. Two new and simple singularity theorems, whose features are different from the classical singularity…

Probability · Mathematics 2011-02-21 Ismael Bailleul

We consider the extent to which we can learn from a completely randomized experiment whether all individuals have treatment effects that are weakly of the same sign, a condition we call monotonicity. From a classical sampling perspective,…

Econometrics · Economics 2026-01-13 Jiafeng Chen , Jonathan Roth , Jann Spiess

Random walks serve as important tools for studying complex network structures, yet their dynamics in cases where transition probabilities are not static remain under explored and poorly understood. Here we study nonlinear random walks that…

Chaotic Dynamics · Physics 2022-06-14 Digesh Chitrakar , Per Sebastian Skardal

This paper proposes a notion of branching bisimilarity for non-deterministic probabilistic processes. In order to characterize the corresponding notion of rooted branching probabilistic bisimilarity, an equational theory is proposed for a…

Logic in Computer Science · Computer Science 2025-02-11 Rob van Glabbeek , Jan Friso Groote , Erik de Vink

Abstract argumentation has emerged as a method for non-monotonic reasoning that has gained popularity in the symbolic artificial intelligence community. In the literature, the different approaches to abstract argumentation that were refined…

Artificial Intelligence · Computer Science 2021-01-11 Timotheus Kampik , Juan Carlos Nieves

We consider the Bayesian analysis of models in which the unknown distribution of the outcomes is specified up to a set of conditional moment restrictions. The nonparametric exponentially tilted empirical likelihood function is constructed…

Statistics Theory · Mathematics 2021-10-27 Siddhartha Chib , Minchul Shin , Anna Simoni

The definition of the conditional probability is very important in the theory of the probability. This definition is based on the fact, that random events can be simultaneously measurable. This paper deal with the problem of conditioning…

Mathematical Physics · Physics 2009-11-10 Olga Nanasiova

In this paper we investigate the complexity-theoretical aspects of cyclic and non-wellfounded proofs in the context of parsimonious logic, a variant of linear logic where the exponential modality ! is interpreted as a constructor for…

Logic in Computer Science · Computer Science 2025-09-12 Matteo Acclavio , Gianluca Curzi , Giulio Guerrieri

We describe a mathematical language for determining all possible patterns of contextuality in the dependence of stochastic outputs of a system on its deterministic inputs. The central notion is that of all possible couplings for…

Mathematical Physics · Physics 2015-01-27 Ehtibar N. Dzhafarov , Janne V. Kujala

In this paper we propose a general approach to define a many-valued preferential interpretation of gradual argumentation semantics. The approach allows for conditional reasoning over arguments and boolean combination of arguments, with…

Artificial Intelligence · Computer Science 2025-06-10 Mario Alviano , Laura Giordano , Daniele Theseider Dupré

This paper investigates natural conditions for the existence of optimal policies for a Markov decision process with incomplete information (MDPII) and with expected total costs. The MDPII is the classic model of a controlled stochastic…

Optimization and Control · Mathematics 2021-09-30 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

We take another look at the general problem of selecting a preferred probability measure among those that comply with some given constraints. The dominant role that entropy maximization has obtained in this context is questioned by arguing…

Artificial Intelligence · Computer Science 2013-02-01 Manfred Jaeger

Probability theory, epistemically interpreted, provides an excellent, if not the best available account of inductive reasoning. This is so because there are general and definite rules for the change of subjective probabilities through…

Artificial Intelligence · Computer Science 2013-04-10 Wolfgang Spohn

Inspired by empirical work in neuroscience for Bayesian approaches to brain function, we give a unified probabilistic account of various types of symbolic reasoning from data. We characterise them in terms of formal logic using the…

Artificial Intelligence · Computer Science 2026-02-24 Hiroyuki Kido

This paper presents an approach for developing the explanation capabilities of rule-based expert systems managing imprecise and uncertain knowledge. The treatment of uncertainty takes place in the framework of possibility theory where the…

Artificial Intelligence · Computer Science 2013-04-08 Henri Farrency , Henri Prade

Termination is one of the basic liveness properties, and we study the termination problem for probabilistic programs with real-valued variables. Previous works focused on the qualitative problem that asks whether an input program terminates…

Programming Languages · Computer Science 2016-11-17 Krishnendu Chatterjee , Petr Novotný , Đorđe Žikelić

We introduce proper display calculi for basic monotonic modal logic,the conditional logic CK and a number of their axiomatic extensions. These calculi are sound, complete, conservative and enjoy cut elimination and subformula property. Our…

In this paper a conditional logic is defined and studied. This conditional logic, DmBL, is constructed as close as possible to the Bayesian and is unrestricted, that is one is able to use any operator without restriction. A notion of…

Logic · Mathematics 2016-09-07 Frederic Dambreville

Logics with team semantics provide alternative means for logical characterization of complexity classes. Both dependence and independence logic are known to capture non-deterministic polynomial time, and the frontiers of tractability in…

Logic in Computer Science · Computer Science 2019-03-27 Miika Hannula , Lauri Hella

The combination of argumentation and probability paves the way to new accounts of qualitative and quantitative uncertainty, thereby offering new theoretical and applicative opportunities. Due to a variety of interests, probabilistic…

Artificial Intelligence · Computer Science 2018-03-12 Regis Riveret , Pietro Baroni , Yang Gao , Guido Governatori , Antonino Rotolo , Giovanni Sartor
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