This program generates a truth-table given a well-formed formula in propositional logic. The table can be printed to the terminal or saved as a HTML file.
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Updated
Aug 31, 2024 - Python
This program generates a truth-table given a well-formed formula in propositional logic. The table can be printed to the terminal or saved as a HTML file.
Equivalence checker for contextual formulas
This project focuses on the intersection of propositional logic, set theory, and Boolean algebra. We have developed a program that enables users to convert propositional expressions—containing variables, conjunctions, disjunctions, negations, and truth values—into various forms, including dual, set notation, and Boolean expression
Implements the Tsetlin Machine, Coalesced Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features, drop clause, Type III Feedback, focused negative sampling, multi-task classifier, autoencoder, literal budget, and one-vs-one multi-class classifier. TMU is writ…
Python package that provides an interface to work with classical propositional and first-order logic, based on my solutions to the textbook Mathematical Logic Through Python by Nisan and Gonczarowski
Analytic tableau based minimal model generator, model checker and theorem prover for first-order logic with modal extensions
The primary purpose of this software is to parse propositional logic formulas and subsequently generate a visually formatted output as well as an image representation of the Abstract Syntax Tree (AST) in PNG format.
A Logic of Relational Propositions
A Python program that solves Knights and Knaves logic puzzles using propositional logic and model-checking algorithms. Determine the truthfulness of characters based on their statements to solve these classic logic puzzles.
Knowledge representation algorithms for bayesian networks and propositional logic
Python library for computational formal logic, formal semantics, and theorem proving
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Python solutions for Introduction to AI laboratory exercises.
Search, Knowledge, Uncertainty, Optimization, Learning, Neural Networks and Language.
Performs normal form conversions of propositional formulas through the use of syntax trees, and provides 3 sat-solver algorithms with verifiable step-by-step output.
Logic for Computer Science, Course Repository, IITD 7th Semester 2023-24
Python project developed using propositional logic and SAT solvers to address problems that can be formulated through propositional logic, applied to a 5x5 nonogram puzzle.
MIRROR of https://codeberg.org/catseye/Maxixe : A simple proof checker
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