Answer set programming is a declarative programming paradigm rooted in non-monotonic logic and stable model semantics, primarily employed for knowledge representation and solving combinatorial search and constraint satisfaction problems. It investigates the use of logic programs, often with negation as failure, where sets of atoms called answer sets (or stable models) represent the problem's solutions or alternative valid states of affairs, offering a robust framework for reasoning with incomplete or changing information.