This document provides an overview of different knowledge representation structures used in artificial intelligence, including associative networks, frame structures, conceptual dependencies, and scripts. Associative networks are neural network models that represent information as activity patterns across neurons. Frame structures represent stereotypical situations as frames with slots and facets to define classes and instances. Conceptual dependency theory represents language using basic representational tokens and conceptual transitions. Script theory proposes that human behavior falls into patterns called scripts that provide programs for common actions and experiences.