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Related papers: Rational Nonmonotonic Reasoning

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Argumentation is the process of constructing arguments about propositions, and the assignment of statements of confidence to those propositions based on the nature and relative strength of their supporting arguments. The process is modelled…

Artificial Intelligence · Computer Science 2013-03-08 John Fox , Paul J. Krause , Morten Elvang-Gøransson

Language technologies that accurately model the dynamics of events must perform commonsense reasoning. Existing work evaluating commonsense reasoning focuses on making inferences about common, everyday situations. To instead investigate the…

Computation and Language · Computer Science 2024-05-02 Wenting Zhao , Justin T Chiu , Jena D. Hwang , Faeze Brahman , Jack Hessel , Sanjiban Choudhury , Yejin Choi , Xiang Lorraine Li , Alane Suhr

A scientific reasoning system makes decisions using objective evidence in the form of independent experimental trials, propositional axioms, and constraints on the probabilities of events. As a first step towards this goal, we propose a…

Artificial Intelligence · Computer Science 2013-04-05 David Sher

In this paper the theory of semi-bounded rationality is proposed as an extension of the theory of bounded rationality. In particular, it is proposed that a decision making process involves two components and these are the correlation…

Artificial Intelligence · Computer Science 2013-05-28 Tshilidzi Marwala

We present a method for relevance sensitive non-monotonic inference from belief sequences which incorporates insights pertaining to prioritized inference and relevance sensitive, inconsistency tolerant belief revision. Our model uses a…

Artificial Intelligence · Computer Science 2016-08-31 Samir Chopra , Konstantinos Georgatos , Rohit Parikh

Tarski gave a general semantics for deductive reasoning: a formula a may be deduced from a set A of formulas iff a holds in all models in which each of the elements of A holds. A more liberal semantics has been considered: a formula a may…

Artificial Intelligence · Computer Science 2007-05-23 Daniel Lehmann

Justification theory is an abstract unifying formalism that captures semantics of various non-monotonic logics. One intriguing problem that has received significant attention is the consistency problem: under which conditions are…

Artificial Intelligence · Computer Science 2022-08-08 Simon Marynissen , Bart Bogaerts

The process of doing Science in condition of uncertainty is illustrated with a toy experiment in which the inferential and the forecasting aspects are both present. The fundamental aspects of probabilistic reasoning, also relevant in real…

History and Overview · Mathematics 2018-02-07 Giulio D'Agostini

In this paper an approach to automated deduction under uncertainty,based on possibilistic logic, is proposed ; for that purpose we deal with clauses weighted by a degree which is a lower bound of a necessity or a possibility measure,…

Artificial Intelligence · Computer Science 2013-04-08 Didier Dubois , Jerome Lang , Henri Prade

The purpose of the paper is to introduce a new approach of planning called Assumption-Based Planning. This approach is a very interesting way to devise a planner based on a multi-agent system in which the production of a global shared plan…

Artificial Intelligence · Computer Science 2018-10-22 Damien Pellier , Humbert Fiorino

This paper considers KLM-style preferential non-monotonic reasoning in the setting of propositional team semantics. We show that team-based propositional logics naturally give rise to cumulative non-monotonic entailment relations. Motivated…

Artificial Intelligence · Computer Science 2024-05-14 Kai Sauerwald , Juha Kontinen

Common knowledge/belief in rationality is the traditional standard assumption in analysing interaction among agents. This paper proposes a graph-based language for capturing significantly more complicated structures of higher-order beliefs…

Artificial Intelligence · Computer Science 2024-12-13 Qi Shi , Pavel Naumov

In this paper we make a contribution to the unification of formal models of defeasible reasoning. We present several translations between formal argumentation frameworks and nonmonotonic logics for reasoning with plausible assumptions. More…

Artificial Intelligence · Computer Science 2016-04-04 Jesse Heyninck , Christian Straßer

A number of writers(Joseph Halpern and Fahiem Bacchus among them) have offered semantics for formal languages in which inferences concerning probabilities can be made. Our concern is different. This paper provides a formalization of…

Artificial Intelligence · Computer Science 2013-03-25 Henry E. Kyburg

The quality of rationales is essential in the reasoning capabilities of language models. Rationales not only enhance reasoning performance in complex natural language tasks but also justify model decisions. However, obtaining impeccable…

Computation and Language · Computer Science 2025-03-05 Hazel H. Kim

There are several contexts of non-monotonic reasoning where a priority between rules is established whose purpose is preventing conflicts. One formalism that has been widely employed for non-monotonic reasoning is the sceptical one known as…

Artificial Intelligence · Computer Science 2012-11-26 Guido Governatori , Francesco Olivieri , Simone Scannapieco , Matteo Cristani

Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the…

Artificial Intelligence · Computer Science 2014-07-29 Joseph Y. Halpern , Riccardo Pucella

A simple framework for reasoning under uncertainty and intervention is introduced. This is achieved in three steps. First, logic is restated in set-theoretic terms to obtain a framework for reasoning under certainty. Second, this framework…

Statistics Theory · Mathematics 2010-08-18 Pedro A. Ortega

The concept of movable evidence masses that flow from supersets to subsets as specified by experts represents a suitable framework for reasoning under uncertainty. The mass flow is controlled by specialization matrices. New evidence is…

Artificial Intelligence · Computer Science 2013-03-26 Rudolf Kruse , Detlef Nauck , Frank Klawonn

The ability to reason under uncertainty and with incomplete information is a fundamental requirement of decision support technology. In this paper we argue that the concentration on theoretical techniques for the evaluation and selection of…

Artificial Intelligence · Computer Science 2013-03-26 John Fox , Paul J. Krause