Inference Rules, Degrees of Truthfulness and Tautologies in Multivalued Hierarchical Logic with One Real and Two Imaginary Logical Structures

2021 ◽  
Author(s):  
Vassil Sgurev
Keyword(s):  
Inference Rules ◽  
Logical Structures

Explanatory Power for Medical Expert Systems: Studies in the Representation of Causal Relationships for Clinical Consultations

1982 ◽  
Vol 21 (03) ◽  
pp. 127-136 ◽  
Author(s):  
J. W. Wallis ◽  
E. H. Shortliffe
Keyword(s):  
Explanatory Power ◽  
Prototype System ◽  
Inference Rules ◽  
Medical Expert ◽  
Comprehensive Knowledge ◽  
Different Types ◽  
Medical Expert Systems ◽  
Explanation System ◽  
Systems Studies

This paper reports on experiments designed to identify and implement mechanisms for enhancing the explanation capabilities of reasoning programs for medical consultation. The goals of an explanation system are discussed, as is the additional knowledge needed to meet these goals in a medical domain. We have focussed on the generation of explanations that are appropriate for different types of system users. This task requires a knowledge of what is complex and what is important; it is further strengthened by a classification of the associations or causal mechanisms inherent in the inference rules. A causal representation can also be used to aid in refining a comprehensive knowledge base so that the reasoning and explanations are more adequate. We describe a prototype system which reasons from causal inference rules and generates explanations that are appropriate for the user.

Boolean-valued structures

2018 ◽  
Author(s):  
Tim Button ◽  
Sean Walsh
Keyword(s):  
Model Theory ◽  
Order Logic ◽  
First Order Logic ◽  
Inference Rules ◽  
Mathematical Concepts ◽  
Semantic Framework ◽  
First Order ◽  
Standard Models ◽  
Boolean Valued Model ◽  
Semantic Values

Chapters 6-12 are driven by questions about the ability to pin down mathematical entities and to articulate mathematical concepts. This chapter is driven by similar questions about the ability to pin down the semantic frameworks of language. It transpires that there are not just non-standard models, but non-standard ways of doing model theory itself. In more detail: whilst we normally outline a two-valued semantics which makes sentences True or False in a model, the inference rules for first-order logic are compatible with a four-valued semantics; or a semantics with countably many values; or what-have-you. The appropriate level of generality here is that of a Boolean-valued model, which we introduce. And the plurality of possible semantic values gives rise to perhaps the ‘deepest’ level of indeterminacy questions: How can humans pin down the semantic framework for their languages? We consider three different ways for inferentialists to respond to this question.

Algorithmic Logic with Recursive Functions

1981 ◽  
Vol 4 (4) ◽  
pp. 975-995
Author(s):  
Andrzej Szałas
Keyword(s):  
Completeness Theorem ◽  
Inference Rules ◽  
Partial Correctness ◽  
Recursive Functions ◽  
Algorithmic Logic ◽  
Block Structured

A language is considered in which the reader can express such properties of block-structured programs with recursive functions as correctness and partial correctness. The semantics of this language is fully described by a set of schemes of axioms and inference rules. The completeness theorem and the soundness theorem for this axiomatization are proved.

Plausibility and Aesthetic Interpretation

1977 ◽  
Vol 7 (2) ◽  
pp. 327-340 ◽  
Author(s):  
Denis Dutton
Keyword(s):  
Scientific Inquiry ◽  
The Other ◽  
Inquiry Science ◽  
Works Of Art ◽  
Different Types ◽  
Logical Structures ◽  
The One

If a catalogue were made of terms commonly used to affirm the adequacy of critical interpretations of works of art, one word certain to be included would be “plausible.” Yet this term is one which has received precious little attention in the literature of aesthetics. This is odd, inasmuch as I find the notion of plausibility central to an understanding of the nature of criticism. “Plausible” is a perplexing term because it can have radically different meanings depending on the circumstances of its employment. ln the following discussion, I will make some observations about the logic of this concept in connection with its uses in two rather different contexts: the context of scientific inquiry on the one hand, and that of aesthetic interpretation on the other. In distinguishing separate senses of “plausible,” I shall provide reason to resist the temptation to imagine that because logical aspects of two different types of inquiry—science and criticism—happen to be designated by the same term, they may to that extent be considered to have similar logical structures.

Inference rules using local contexts

1988 ◽  
Vol 4 (4) ◽  
pp. 445-462 ◽  
Author(s):  
Leonard G. Monk
Keyword(s):  
Inference Rules ◽  
Local Contexts

Ontological Knowledge Representation and Inference Rules for MTM Decision Support System

2014 ◽  
Author(s):  
Rahul Renu ◽  
Gregory Mocko
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Representation ◽  
Support System ◽  
Time Estimation ◽  
Time Measurement ◽  
Inference Rules ◽  
Assembly Time ◽  
Time Estimates ◽  
Definition Of

The objective of the research presented is to develop and implement an ontological knowledge representation for Methods-Time Measurement assembly time estimation process. The knowledge representation is used to drive a decision support system that provides the user with intelligent MTM table suggestions based on assembly work instructions. Inference rules are used to map work instructions to MTM tables. An explicit definition of the assembly time estimation domain is required. The contribution of this research, in addition to the decision support system, is an extensible knowledge representation that models work instructions, MTM tables and mapping rules between the two which will enable the establishment of assembly time estimates. Further, the ontology provides an extensible knowledge representation framework for linking time studies and assembly processes.

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