This paper reviews work on the representation of knowledge from within psychology and artificial intelligence. The work covers the nature of representation, the distinction between the represented world and the representing world, and significant issues concerned with propositional, analogical, and superpositional representations. Specific topics related to propositionally-based systems are semantic features or attributes, symbolic logic and the predicate calculus, semantic networks and their properties, schemata and frames, and the relationship of these representations to classical associations. A section on analogical representations discusses the work of Shepard, Kosslyn, and Funt; mental models and mental simulations; and propositional and analogical representation. Procedural representation topics addressed include the human information processing system, procedural representation, and demons and production systems. Additional topics include local and superpositional memory systems, associative memories, cognition and categorization, and generalization. Major controversies within psychology--such as distinctions between declarative and procedural representation, propositional and analogical representation and the nature of visual images--are analyzed and found not to reflect fundamental disagreements. A five-page reference list is included. (Author/LMM).