scholarly journals A General Framework for Ampliative Inference Patterns

1998 ◽  
Vol 1 (2) ◽  
Author(s):  
Claudio Delrieux
Keyword(s):  
Expert Systems ◽  
Intelligent Systems ◽  
General Framework ◽  
General Pattern ◽  
Nonmonotonic Reasoning ◽  
Reasoning Systems ◽  
Research Programmes ◽  
Complete Procedure ◽  
Information Errors ◽  
Ampliative Inference

Non trivial reasoning from contradictory premises is being acknowledged as one of the most important features in intelligent systems. Expert systems, planners and schedulers, and diagnosers, are almost always faced to potentially fallacious information, errors, uncertainty, and difference of opinions. In thesecases, we expect that the reasoning systems will not collapse. Instead, the rational expected behavior is to isolate the source of contradiction. Several systems for reasoning from contradictory premises have been advanced, usually within acontext of strict, monotonic knowledge. In this work we investigate how defeasible knowledge can be also handled in these systems. The key idea is to represent pieces of defeasible knowledge ordered within anepistemic importance relation. A semantic characterization is provided, and a sound and complete procedure to compute conclusions is also given. Then, we show how nonmonotonic reasoning and other patterns of ampliative inference like abduction and induction can be adequately recast within the general pattern of reasoning from contradiction. We discuss some applications, in particular, a brief formalization of scientific research programmes. 

scholarly journals A General Framework for Ampliative Inference Patterns

1998 ◽  
Vol 1 (2) ◽  
Author(s):  
Claudio Delrieux
Keyword(s):  
Expert Systems ◽  
Intelligent Systems ◽  
General Framework ◽  
General Pattern ◽  
Nonmonotonic Reasoning ◽  
Reasoning Systems ◽  
Research Programmes ◽  
Complete Procedure ◽  
Information Errors ◽  
Ampliative Inference

Non trivial reasoning from contradictory premises is being acknowledged as one of the most important features in intelligent systems. Expert systems, planners and schedulers, and diagnosers, are almost always faced to potentially fallacious information, errors, uncertainty, and difference of opinions. In thesecases, we expect that the reasoning systems will not collapse. Instead, the rational expected behavior is to isolate the source of contradiction. Several systems for reasoning from contradictory premises have been advanced, usually within acontext of strict, monotonic knowledge. In this work we investigate how defeasible knowledge can be also handled in these systems. The key idea is to represent pieces of defeasible knowledge ordered within anepistemic importance relation. A semantic characterization is provided, and a sound and complete procedure to compute conclusions is also given. Then, we show how nonmonotonic reasoning and other patterns of ampliative inference like abduction and induction can be adequately recast within the general pattern of reasoning from contradiction. We discuss some applications, in particular, a brief formalization of scientific research programmes. 

Formalization of Inheritance Reasoning in Autoepistemic Logic

1990 ◽  
Vol 13 (4) ◽  
pp. 403-443
Author(s):  
Michael Gelfond ◽  
Halina Przymusinska
Keyword(s):  
General Framework ◽  
Nonmonotonic Reasoning ◽  
Commonsense Reasoning ◽  
Autoepistemic Logic

Current research in the area of nonmonotonic reasoning suggests that autoepistemic logic provides a general framework for formalizing commonsense reasoning in various domains of discourse. The goal of this paper is to investigate the suitability of autoepistemic logic for formalization of some forms of inheritance reasoning. To this end we propose a new semantics for inheritance networks with exceptions based on autoepistemic logic.

scholarly journals Characterization of logic program revision as an extension of propositional revision

2015 ◽  
Vol 16 (1) ◽  
pp. 111-138 ◽  
Author(s):  
NICOLAS SCHWIND ◽  
KATSUMI INOUE
Keyword(s):  
Logic Program ◽  
Nonmonotonic Reasoning ◽  
Knowledge Representation And Reasoning ◽  
Logic Programs ◽  
Characterization Result ◽  
International Conference ◽  
Complete Procedure ◽  
Boolean Lattices ◽  
Computational Properties

AbstractWe address the problem of belief revision of logic programs (LPs), i.e., how to incorporate to a LP P a new LP Q. Based on the structure of SE interpretations, Delgrande et al. (2008. Proc. of the 11th International Conference on Principles of Knowledge Representation and Reasoning (KR'08), 411–421; 2013b. Proc. of the 12th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR'13), 264–276) adapted the well-known AGM framework (Alchourrón et al. 1985. Journal of Symbolic Logic 50, 2, 510–530) to LP revision. They identified the rational behavior of LP revision and introduced some specific operators. In this paper, a constructive characterization of all rational LP revision operators is given in terms of orderings over propositional interpretations with some further conditions specific to SE interpretations. It provides an intuitive, complete procedure for the construction of all rational LP revision operators and makes easier the comprehension of their semantic and computational properties. We give a particular consideration to LPs of very general form, i.e., the generalized logic programs (GLPs). We show that every rational GLP revision operator is derived from a propositional revision operator satisfying the original AGM postulates. Interestingly, the further conditions specific to GLP revision are independent from the propositional revision operator on which a GLP revision operator is based. Taking advantage of our characterization result, we embed the GLP revision operators into structures of Boolean lattices, that allow us to bring to light some potential weaknesses in the adapted AGM postulates. To illustrate our claim, we introduce and characterize axiomatically two specific classes of (rational) GLP revision operators which arguably have a drastic behavior. We additionally consider two more restricted forms of LPs, i.e., the disjunctive logic programs (DLPs) and the normal logic programs (NLPs) and adapt our characterization result to disjunctive logic program and normal logic program revision operators.

Fundamentals of creating MIVAR expert systems

2021 ◽  
Author(s):  
Oleg Varlamov
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Intelligent Systems ◽  
Autonomous Robots ◽  
Support Systems ◽  
Knowledge Bases ◽  
Computer Engineering

Methodological and applied issues of the basics of creating knowledge bases and expert systems of logical artificial intelligence are considered. The software package "MIV Expert Systems Designer" (KESMI) Wi!Mi RAZUMATOR" (version 2.1), which is a convenient tool for the development of intelligent information systems. Examples of creating mivar expert systems and several laboratory works are given. The reader, having studied this tutorial, will be able to independently create expert systems based on KESMI. The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

Monotonic and Nonmonotonic Reasoning in Zoom Reasoning Systems

2004 ◽  
pp. 1085-1091 ◽  
Author(s):  
Tetsuya Murai ◽  
M. Sanada ◽  
Yasuo Kudo ◽  
Y. Sato
Keyword(s):  
Nonmonotonic Reasoning ◽  
Reasoning Systems

scholarly journals About some possibilities of diagnosing partial failures arising in complex agricultural machinery

2020 ◽  
Vol 175 ◽  
pp. 05004
Author(s):  
Alexy Zotov ◽  
Vadim Gritsenko ◽  
Andrey Gazizov
Keyword(s):  
Decision Support ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Intelligent Systems ◽  
Diagnostic Procedure ◽  
Agricultural Machinery ◽  
Managerial Decision ◽  
Complex Technical Systems ◽  
Multi Level ◽  
Technical Systems

The article is devoted to the issue of partial failure in complex technical systems. The authors analyze the diagnostic procedure in agricultural machinery for various purposes, the results of which provide a diagram of a multi-level organization for assessing the condition of equipment. It is also proposed to expand the range of estimated diagnostic parameters for making a more reliable managerial decision. The introduction of expert systems and other similar intelligent systems (for example, expert decision support systems) for diagnosing complex malfunctions is justified.

How to Reason about the World

2008 ◽  
pp. 184-198
Author(s):  
Azamat Abdoullaev
Keyword(s):  
Intelligent Systems ◽  
Possible Worlds ◽  
Human Beings ◽  
Intelligent Machines ◽  
The Core ◽  
Reasoning Systems ◽  
The World ◽  
Ontological Ground ◽  
The Difference ◽  
The Universe

Along with substances of all kinds, states of all manner, and changes of all types and exemplifications, relationships of all sorts and instances appear to be among the prime constituents of the universe as a whole and its realms, regions, and domains as the world of nature, the universe of society, and the domain of minds. Hence, knowledge of relations, as the causeeffect relationship, constitutes the basic core of real knowledge and, consequently, the logical fundament for all basic kinds of reasoning about the world. Since all reasoning upon reality, its particular classes, parts and features, is eventually to be founded on the underlying relations of substances, states, changes, and analogies, as well as on the meta-relations of whole-part, comparison, contrast, identity, resemblance, and difference. To adequately represent and consistently reason about reality is vitally important not only for human beings but also for prospective intelligent machines driven by the ontological models of the world comprehending the logical models of possible worlds. A widely practiced logical tradition to represent the world in terms of abstract classes, properties, and relations or purely mathematical objects, functions, and relations looks to be a main conceptual obstacle to creating effective reasoning systems. Since the likewise artificial conceptualizations of the world are missing out the core of things, their nature and reality, providing the ontological ground and making true the truth. These would-be reasoning systems will not work effectively because of their built-in incapacity to work out any complex real problems or situations or challenges. Above all other things, such intelligent systems will be unable to see the difference of physical, mental, or social objects so that to recognize their attributes, qualities, properties, states, changes, and relations.

ON THE COMPLETION OF PRIORITY ORDERINGS IN NONMONOTONIC REASONING SYSTEMS

1993 ◽  
Vol 01 (02) ◽  
pp. 139-165 ◽  
Author(s):  
RONALD R. YAGER
Keyword(s):  
Nonmonotonic Reasoning ◽  
Knowledge Bases ◽  
Weak Order ◽  
Preference Structure ◽  
Preference Theory ◽  
Reasoning Systems ◽  
The One ◽  
Comprehensive Discussion

We discuss the structure of nonmonotonic reasoning. We suggest that an important aspect of nonmonotonic reasoning systems is the ordering relationship (preference structure) on the propositions in the knowledge. We suggest that this ordering relationship must be a weak order, a complete and transitive relationship. We provide a comprehensive discussion of some central issues in preference theory. In most real applications of nonmonotonic knowledge bases the ordering relationship available is often not complete. We suggest a mechanism for completing these relationships. The basic imperative used in providing this completion is to do it in such a manner as to add as few unjustified inferences as necessary. To formally accomplish this task we introduce a measure of buoyancy associated with a weak order and suggest that the preferred completion is the one with the maximal buoyancy.

Formalizing nonmonotonic reasoning systems

1987 ◽  
Vol 31 (1) ◽  
pp. 41-85 ◽  
Author(s):  
David W. Etherington
Keyword(s):  
Nonmonotonic Reasoning ◽  
Reasoning Systems
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