1989/01/01 by Allan Collins, Ryszard S. Michalski · 361 citations
Computer Science · Psychology · #Artificial intelligence #Bayesian Modeling and Causal Inference #Certainty #Cognitive science #Computer science #Construct (python library) #Core (optical fiber) #Epistemology #Inference #Logic, Reasoning, and Knowledge #Psychology #Representation (politics) #Semantic Web and Ontologies #Set (abstract data type) #Similarity (geometry) #Theory
paper · pdf · doi:10.1207/s15516709cog1301_1
published in Cognitive Science 13(1), 1-49 (Wiley)
openalex publication_date 1989/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/05/21
The paper presents a core theory of human plausible reasoning based on analysis of people's answers to everyday questions about the world. The theory consists of three parts: a formal representation of plausible inference patterns; such as deductions, inductions, and analogies, that are frequently employed in answering everyday questions; a set of parameters, such as conditional likelihood, typicality, and similarity, that affect the certainty of people's answers to such questions; and a system relating the different plausible inference patterns and the different certainty parameters. This is one of the first attempts to construct a formal theory that addresses both the semantic and parametric aspects of the kind of everyday reasoning that pervades. all of human discourse.