The judgment stroke and the truth predicate: Frege and the logical representation of judgment

2009 ◽  
pp. 74-102
Author(s):  
Wayne Martin
Keyword(s):  
Truth Predicate ◽  
Logical Representation

scholarly journals NOTES ON BOUNDED INDUCTION FOR THE COMPOSITIONAL TRUTH PREDICATE

2017 ◽  
Vol 10 (3) ◽  
pp. 455-480 ◽  
Author(s):  
BARTOSZ WCISŁO ◽  
MATEUSZ ŁEŁYK
Keyword(s):  
Reflection Principle ◽  
Peano Arithmetic ◽  
Truth Predicate ◽  
Base Theory ◽  
Modified Theory ◽  
Induction Scheme

AbstractWe prove that the theory of the extensional compositional truth predicate for the language of arithmetic with Δ0-induction scheme for the truth predicate and the full arithmetical induction scheme is not conservative over Peano Arithmetic. In addition, we show that a slightly modified theory of truth actually proves the global reflection principle over the base theory.

Tarski

Truth ◽  
2011 ◽  
Author(s):  
Alexis G. Burgess ◽  
John P. Burgess
Keyword(s):  
Mathematical Logic ◽  
Model Theory ◽  
The State ◽  
Truth Predicate ◽  
Object Language ◽  
French And English ◽  
Direct Definition ◽  
Definition Of ◽  
Basic Features ◽  
Self Reference

This chapter offers a simplified account of the most basic features of Alfred Tarski's model theory. Tarski foresaw important applications for a notion of truth in mathematics, but also saw that mathematicians were suspicious of that notion, and rightly so given the state of understanding of it circa 1930. In a series of papers in Polish, German, French, and English from the 1930s onward, Tarski attempted to rehabilitate the notion for use in mathematics, and his efforts had by the 1950s resulted in the creation of a branch of mathematical logic known as model theory. The chapter first considers Tarski's notion of truth, which he calls “semantic” truth, before discussing his views on object language and metalanguage, recursive versus direct definition of the truth predicate, and self-reference.

Modelling Virtual Bargaining using Logical Representation Change

2021 ◽  
pp. 68-90
Author(s):  
Alan Bundy ◽  
Eugene Philalithis ◽  
Xue Li
Keyword(s):  
Information Exchange ◽  
Computational Modelling ◽  
Coordination Game ◽  
Item Selection ◽  
Logic Programs ◽  
Work In Progress ◽  
Initial Work ◽  
Human Participants ◽  
Logical Representation ◽  
Minimal Information

We discuss work in progress on the computational modelling of virtual bargaining: inference-driven human coordination under severe communicative constraints. For this initial work we model variants of a two-player coordination game of item selection and avoidance taken from the current virtual bargaining literature. In this range of games, human participants collaborate to select items (e.g. bananas) or avoid items (e.g. scorpions), based on signalling conventions constructed and updated from shared assumptions, with minimal information exchange. We model behaviours in these games using logic programs interpretable as logical theories. From an initial theory comprised of rules, background assumptions and a basic signalling convention, we use automated theory repair to jointly adapt that basic signalling convention to novel contexts, with no explicit coordination between players. Our ABC system for theory repair delivers spontaneous adaptation, using reasoning failures to replace established conventions with better alternatives, matching human players’ own reasoning across several games.

Soundness, Epistemology, and Frege’s Project

2020 ◽  
pp. 115-169
Author(s):  
Joan Weiner
Keyword(s):  
Natural Language ◽  
Formal System ◽  
Truth Predicate

Insofar as the use of natural language to introduce, discuss, and argue about features of a formal system is metatheoretic, there can be no doubt: Frege has a metatheory. But what kind of metatheory? Although the model theoretic semantics with which we are familiar today is a post-Fregean development, most believe that Frege offers a proto-soundness proof for his logic that intrinsically exploits a truth predicate and metalinguistic variables. In this chapter it is argued that he neither uses, nor has any need to use, a truth predicate or metalinguistic variables in justifications of his basic laws and rules. The purpose of the discussions that are typically understood as constituting Frege’s metatheory is, rather, elucidatory. And once we see what the aim of these particular elucidations is, we can explain Frege’s otherwise puzzling eschewal of the truth predicate in his discussions of the justification of the laws and rules of inference.

scholarly journals Amazon Employees Resources Access Data Extraction via Clonal Selection Algorithm and Logic Mining Approach

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 596 ◽  
Author(s):  
Nur Ezlin Zamri ◽  
Mohd. Asyraf Mansor ◽  
Mohd Shareduwan Mohd Kasihmuddin ◽  
Alyaa Alway ◽  
Siti Zulaikha Mohd Jamaludin ◽  
...  
Keyword(s):  
Neural Network ◽  
Data Science ◽  
Clonal Selection ◽  
Data Extraction ◽  
Hopfield Neural Network ◽  
Clonal Selection Algorithm ◽  
Selection Algorithm ◽  
Proposed Model ◽  
Artificial Neural Network Ann ◽  
Logical Representation

Amazon.com Inc. seeks alternative ways to improve manual transactions system of granting employees resources access in the field of data science. The work constructs a modified Artificial Neural Network (ANN) by incorporating a Discrete Hopfield Neural Network (DHNN) and Clonal Selection Algorithm (CSA) with 3-Satisfiability (3-SAT) logic to initiate an Artificial Intelligence (AI) model that executes optimization tasks for industrial data. The selection of 3-SAT logic is vital in data mining to represent entries of Amazon Employees Resources Access (AERA) via information theory. The proposed model employs CSA to improve the learning phase of DHNN by capitalizing features of CSA such as hypermutation and cloning process. This resulting the formation of the proposed model, as an alternative machine learning model to identify factors that should be prioritized in the approval of employees resources applications. Subsequently, reverse analysis method (SATRA) is integrated into our proposed model to extract the relationship of AERA entries based on logical representation. The study will be presented by implementing simulated, benchmark and AERA data sets with multiple performance evaluation metrics. Based on the findings, the proposed model outperformed the other existing methods in AERA data extraction.

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