Logical Reasoning

Logical reasoning studies how conclusions follow from facts and rules, including deduction, abduction, induction, and reasoning with uncertainty, exceptions, time, or conflicting information. Classical approaches use formal languages, theorem provers, SAT/SMT solvers, Datalog, and description logics; neuro-symbolic systems combine these tools with learned perception or language models. Current work evaluates systems on first-order logic, syllogisms, rule-based decisions, and compositional puzzles, often using solver-verified benchmarks and proof traces. A central challenge is that correct answers can hide invalid or shortcut reasoning, while systems that verify steps still struggle with long, deep, unfamiliar, or alternative reasoning paths.