Uncertain Reasoning in Justification Logic

Uncertain Reasoning in Justification Logic
Author: Ioannis Kokkinis
Publisher: Lulu.com
Total Pages: 116
Release: 2016-06
Genre: Computers
ISBN: 1326645102

This thesis studies the combination of two well known formal systems for knowledge representation: probabilistic logic and justification logic. Our aim is to design a formal framework that allows the analysis of epistemic situations with incomplete information. In order to achieve this we introduce two probabilistic justification logics, which are defined by adding probability operators to the minimal justification logic J. We prove soundness and completeness theorems for our logics and establish decidability procedures. Both our logics rely on an infinitary rule so that strong completeness can be achieved. One of the most interesting mathematical results for our logics is the fact that adding only one iteration of the probability operator to the justification logic J does not increase the computational complexity of the logic.

Justification Logic

Justification Logic
Author: Sergei Artemov
Publisher: Cambridge University Press
Total Pages: 271
Release: 2019-05-02
Genre: Mathematics
ISBN: 1108424910

Develops a new logic paradigm which emphasizes evidence tracking, including theory, connections to other fields, and sample applications.

Reasoning with Actual and Potential Contradictions

Reasoning with Actual and Potential Contradictions
Author: Dov M. Gabbay
Publisher: Springer Science & Business Media
Total Pages: 333
Release: 2013-04-17
Genre: Philosophy
ISBN: 9401717397

We are happy to present the second volume of the Handbook of Defeasible Reasoning and Uncertainty Management Systems. Uncertainty pervades the real world and must therefore be addressed by every system that attempts to represent reality. The representation of un certainty is a major concern of philosophers, logicians, artificial intelligence researchers and computer sciencists, psychologists, statisticians, economists and engineers. The present Handbook volumes provide frontline coverage of this area. This Handbook was produced in the style of previous handbook series like the Handbook of Philosophical Logic, the Handbook of Logic in Computer Science, the Handbook of Logic in Artificial Intelligence and Logic Programming, and can be seen as a companion to them in covering the wide applications of logic and reasoning. We hope it will answer the needs for adequate representations of uncertainty. This Handbook series grew out of the ESPRIT Basic Research Project DRUMS II, where the acronym is made out of the Handbook series title. This project was financially supported by the European Union and regroups 20 major European research teams working in the general domain of uncer tainty. As a fringe benefit of the DRUMS project, the research community was able to create this Handbook series, relying on the DRUMS partici pants as the core of the authors for the Handbook together with external international experts.

Probabilistic Extensions of Various Logical Systems

Probabilistic Extensions of Various Logical Systems
Author: Zoran Ognjanović
Publisher: Springer Nature
Total Pages: 238
Release: 2020-07-17
Genre: Computers
ISBN: 3030529541

The contributions in this book survey results on combinations of probabilistic and various other classical, temporal and justification logical systems. Formal languages of these logics are extended with probabilistic operators. The aim is to provide a systematic overview and an accessible presentation of mathematical techniques used to obtain results on formalization, completeness, compactness and decidability. The book will be of value to researchers in logic and it can be used as a supplementary text in graduate courses on non-classical logics.

The Uncertain Reasoner's Companion

The Uncertain Reasoner's Companion
Author: J. B. Paris
Publisher: Cambridge University Press
Total Pages: 224
Release: 1994
Genre: Computers
ISBN: 0521460891

This is an introduction to the mathematical foundations of uncertain reasoning.

Reasoning Under Incomplete Information In Artificial Intelligence

Reasoning Under Incomplete Information In Artificial Intelligence
Author: Léa Sombé
Publisher:
Total Pages: 168
Release: 1990-09-10
Genre: Computers
ISBN:

The formalization of ``revisable reasoning'' has been the object of numerous works, developed independently and using many diverse approaches--approaches that are purely symbolic, use numbers to quantify uncertainty, are close to formal logic or less formalized; some deal with exceptions, and a smaller number consider the problem of knowledge bases of revision. This work presents and compares several of these revisable (incomplete) reasoning methods for use in AI. Each method is systematically evaluated with a single example to give the reader an appreciation of the rationale and use of each formulation. The logics considered include: default logic, non-monotonic modal logics, the supposition-based logic, the conditional logics, and the logics of uncertainty. The book also discusses the contribution of works on truth maintenance and logic of action.

Theory of Graded Consequence

Theory of Graded Consequence
Author: Mihir Kumar Chakraborty
Publisher: Springer
Total Pages: 224
Release: 2020-08-14
Genre: Philosophy
ISBN: 9789811389870

This book introduces the theory of graded consequence (GCT) and its mathematical formulation. It also compares the notion of graded consequence with other notions of consequence in fuzzy logics, and discusses possible applications of the theory in approximate reasoning and decision-support systems. One of the main points where this book emphasizes on is that GCT maintains the distinction between the three different levels of languages of a logic, namely object language, metalanguage and metametalanguage, and thus avoids the problem of violation of the principle of use and mention; it also shows, gathering evidences from existing fuzzy logics, that the problem of category mistake may arise as a result of not maintaining distinction between levels.

Logical Foundations of Computer Science

Logical Foundations of Computer Science
Author: Sergei Artemov
Publisher: Springer
Total Pages: 378
Release: 2017-12-22
Genre: Mathematics
ISBN: 3319720562

This book constitutes the refereed proceedings of the International Symposium on Logical Foundations of Computer Science, LFCS 2018, held in Deerfield Beach, FL, USA, in January 2018. The 22 revised full papers were carefully reviewed and selected from 22 submissions. The scope of the Symposium is broad and includes constructive mathematics and type theory; homotopy type theory; logic, automata, and automatic structures; computability and randomness; logical foundations of programming; logical aspects of computational complexity; parameterized complexity; logic programming and constraints; automated deduction and interactive theorem proving; logical methods in protocol and program verification; logical methods in program specification and extraction; domain theory logics; logical foundations of database theory; equational logic and term rewriting; lambda andcombinatory calculi; categorical logic and topological semantics; linear logic; epistemic and temporal logics; intelligent and multiple-agent system logics; logics of proof and justification; non-monotonic reasoning; logic in game theory and social software; logic of hybrid systems; distributed system logics; mathematical fuzzy logic; system design logics; and other logics in computer science.

Dynamics, Uncertainty and Reasoning

Dynamics, Uncertainty and Reasoning
Author: Beishui Liao
Publisher: Springer
Total Pages: 207
Release: 2019-07-23
Genre: Philosophy
ISBN: 981137791X

This volume collects selected papers presented at the Second Chinese Conference on Logic and Argumentation in 2018 held in Hangzhou, China. The papers presented reflect recent advances in logic and argumentation, as well as the connections between the two, and also include invited papers contributed by leading experts in these fields. The book covers a wide variety of topics related to dynamics, uncertainty and reasoning. It continues discussions on the interplay between logic and argumentation which has a long history from Aristotle’s ancient logic to very recent formal argumentation in AI.