It extends propositional logic by introducing variables, ... A classic example is the use of Prolog, a programming language based on predicate logic, for creating rule-based AI systems.

Programming paradigms, languages, compilers, linters, automated validation scripts are based on foundations of formal logic including axioms, syllogisms, predicate and propositional calculus and ...

In this project, we will write a Python program that generates the "truth table" for a set of Boolean variables (i.e. all possible assignments of T/F to those variables) for each row of the truth ...

Handbook of Practical Logic and Automated Reasoning is a book designed to teach the fundamental aspects of propositional logic, automated theorem proving, and proof assistants. It includes a large ...

These diagrams outline the different steps of the propositional logic and classical planning processes. Notice that the process is the same but the representation of states and actions are different.

In the Logic Extraction phase, LLMs identify sentences with conditional reasoning relationships and extract propositional symbols and logical expressions from the input context. The Logic Extension ...

In this paper, we codify a set of invariant patterns formalized for capturing a rich category of propositional constraints on class diagrams. We use tools of Boolean logic to set out the distinction ...

Logic programming inspired several designs for DNA-based inference systems 14,15,17,18, including an example of laboratory-scale DNA computing with a human-assisted protocol 16.

Knowledge representation and reasoning in logic programming constitute a core area of artificial intelligence that formalises how information is symbolically encoded and manipulated.