Mental Models: A Survey

This paper reviews a class of cognitive representations collectively known as mental models. These representations purport to integrate certain aspects of propositional and imagistic theories of knowledge representation while enabling more detailed theories of human cognitive behavior. This paper explores the nature of mental models by considering basic philosophical issues including ontology and semantics. Psychological evidence supporting the existence and identifying characteristics of these models are reviewed in the areas of comprehension, problem solving, and learning. Where available, computational implementations of mental model theories are discussed. After a comparison of mental models with more conventional knowledge representations, a brief discussion and directions for future research are given.

[1]  Barbara Y. White,et al.  Intelligent Tutoring Systems Based Upon Qualitative Model Evolutions , 1986, AAAI.

[2]  R. Doyle.  Hypothesizing Device Mechanisms: Opening Up the Black Box , 1988 .

[3]  M. McCloskey.  Naive Theories of Motion. , 1982 .

[4]  Benny Shanon,et al.  Semantic representation of meaning: A critique. , 1988 .

[5]  H. Gelernter,et al.  Realization of a geometry theorem proving machine , 1995, IFIP Congress.

[6]  Aaron Sloman,et al.  Interactions Between Philosophy and Artificial Intelligence: The Role of Intuition and Non-Logical Reasoning in Intelligence , 1971, IJCAI.

[7]  Terry Winograd,et al.  Understanding natural language , 1974 .

[8]  G. Boolos.  On ‘syllogistic inference’ , 1984, Cognition.

[9]  Hartry Field.  Mental representation , 2021, Encyclopedia of Autism Spectrum Disorders.

[10]  Patrick J. Hayes,et al.  Naive physics I: ontology for liquids , 1989 .

[11]  Elizabeth C. Hirschman,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[12]  J. S. Brown,et al.  Pedagogical, natural language, and knowledge engineering techniques in SOPHIE-I, II and III , 1982 .

[13]  Rogers P. Hall,et al.  Computational Approaches to Analogical Reasoning: A Comparative Analysis , 1989, Artif. Intell..

[14]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[15]  W. H. F. Barnes.  The Nature of Explanation , 1944, Nature.

[16]  R. Young.  Surrogates and mappings: two kinds of conceptual models for interactive , 1983 .

[17]  Sanjaya Addanki,et al.  Reasoning About Assumptions in Graphs of Models , 1989, IJCAI.

[18]  Donald A. Norman,et al.  Some observations on mental models , 1987 .

[19]  John D. Bransford,et al.  A sketch of a cognitive approach to comprehension: Some thoughts about understanding what it means to comprehend. , 1974 .

[20]  Donald A. Norman,et al.  Representation in Memory. , 1983 .

[21]  J. Greeno.  Situations, mental models, and generative knowledge. , 1989 .

[22]  Kenneth D. Forbus,et al.  Learning Physical Domains: Toward a Theoretical Framework. , 1986 .

[23]  John H. Holland,et al.  Induction: Processes of Inference, Learning, and Discovery , 1987, IEEE Expert.

[24]  Aaron Sloman,et al.  Afterthoughts on Analogical Representations , 1975, TINLAP.

[25]  John B. Kidd,et al.  Judgement under Uncertainty: Heuristics and Biasses , 1983 .

[26]  R. Finke,et al.  Principles of mental imagery , 1989 .

[27]  Henry Montgomery,et al.  Mental models and problem solving: Three challenges to a theory of restructuring and insight , 1988 .

[28]  M. Burstein.  Combining Analogies in Mental Models , 1988 .

[29]  David L. Waltz.  Generating and Understanding Scene Descriptions. , 1980 .

[30]  L. Rips.  Cognitive Processes in Propositional Reasoning. , 1983 .

[31]  Thomas P. Moran,et al.  Mental models and problem solving in using a calculator , 1983, CHI '83.

[32]  S. Kosslyn.  The medium and the message in mental imagery: A theory. , 1981 .

[33]  Judith D. Wilson,et al.  Artificial Intelligence and Tutoring Systems , 1990 .

[34]  John D. Bransford,et al.  Considerations of some problems of comprehension. , 1973 .

[35]  Dean Allemang,et al.  Exploring the No-Function-In-Structure principle , 1989, J. Exp. Theor. Artif. Intell..

[36]  A. Garnham.  Mental models as representations of discourse and text , 1989 .

[37]  A. Tversky,et al.  The simulation heuristic , 1982 .

[38]  John R. Anderson.  Methodologies for studying human knowledge , 1987, Behavioral and Brain Sciences.

[39]  N. M. Morris,et al.  On Looking into the Black Box: Prospects and Limits in the Search for Mental Models , 1986 .

[40]  Randall Davis,et al.  Model-based reasoning: troubleshooting , 1988 .

[41]  W. Kintsch,et al.  Strategies of discourse comprehension , 1983 .

[42]  D. Kibler,et al.  Exploring the Episodic Structure of Algebra Story Problem Solving , 1989 .

[43]  Daniel G. Bobrow,et al.  Qualitative Reasoning about Physical Systems: An Introduction , 1984, Artif. Intell..

[44]  John R. Anderson.  Arguments concerning representations for mental imagery. , 1978 .

[45]  Kenneth D. Forbus.  Qualitative Reasoning About Space and Motion , 1983 .

[46]  C. Lewis.  A model of mental model construction , 1986, CHI '86.

[47]  Benjamin Kuipers,et al.  Modeling Spatial Knowledge , 1978, IJCAI.

[48]  Johan de Kleer,et al.  An Assumption-Based TMS , 1987, Artif. Intell..

[49]  Roger C. Schank,et al.  SCRIPTS, PLANS, GOALS, AND UNDERSTANDING , 1988 .

[50]  David Macaulay,et al.  The Way Things Work , 1988 .

[51]  R. K. Lindsay.  Images and inference , 1988, Cognition.

[52]  Patrick J. Hayes,et al.  Some problems and non-problems in representation theory , 1974 .

[53]  Colin Potts,et al.  Design of Everyday Things , 1988 .

[54]  Randall Davis,et al.  Diagnostic Reasoning Based on Structure and Behavior , 1984, Artif. Intell..

[55]  Kenneth Dale Forbus.  A Study of Qualitative and Geometric Knowledge in Reasoning about Motion. Revision. , 1981 .

[56]  Brian V. Funt,et al.  Problem-Solving with Diagrammatic Representations , 1980, Artif. Intell..

[57]  J. Fodor,et al.  The structure of a semantic theory , 1963 .