reasoner

A reasoner is a software component that derives new information from a set of asserted facts and rules according to a formal logic. Reasoners are central to knowledge representation, automated deduction, and semantic processing in artificial intelligence. They may operate over different logical formalisms, including propositional logic, first-order logic, description logics, or equational theories, and they are often integrated into larger systems such as theorem provers, proof assistants, or ontology editors.

Reasoners differ in approach. Deductive reasoners apply inference rules, using techniques such as forward chaining, backward chaining, resolution, or tableaux to generate consequences or prove conjectures. Model checkers explore whether a system satisfies a specification by examining possible states, and constraint or SMT solvers search for assignments to variables that meet all constraints. Practical systems typically balance expressiveness with decidability and performance, yielding complete or incomplete reasoning depending on the logic.

Applications include formal verification of software and hardware, program analysis, knowledge representation, and ontology reasoning. In the semantic web, OWL reasoners (for example HermiT, Pellet, or FaCT++) infer class hierarchies and property relationships from ontologies. Prolog-style engines perform logic programming with backtracking. SMT/SAT solvers such as Z3 or CVC4 are used to discharge logical constraints in verification and synthesis tasks.

Overall, a reasoner is a core tool for deriving implicit information, checking consistency, and supporting automated decision-making within deductive frameworks. Challenges include scalability, non-monotonic reasoning, and handling expressive logics while preserving tractability.