Logic Programming (LP) stands as a cornerstone in the realm of Artificial Intelligence (AI), offering powerful tools for knowledge representation, reasoning and problem-solving. This paper delves into the intricate landscape of LP within AI, elucidating its foundational principles, essential algorithms and diverse applications. Beginning with a primer on LP, we traverse through its historical evolution, highlighting key milestones and pivotal developments. Subsequently, we dissect fundamental LP paradigms, such as Prolog, Constraint Logic Programming (CLP) and Answer Set Programming (ASP), elucidating their unique features and operational mechanisms.
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