Skip to main content
Log in

The cognitive adequacy of Allen's interval calculus for qualitative spatial representation and reasoning

  • Published:
Spatial Cognition and Computation

Abstract

Qualitative spatial reasoning (QSR) is often claimed to be cognitively more plausible than conventional numerical approaches to spatial reasoning, because it copes with the indeterminacy of spatial data and allows inferences based on incomplete spatial knowledge. The paper reports experimental results concerning the cognitive adequacy of an important approach used in QSR, namely the spatial interpretation of the interval calculus introduced by Allen (1983). Knauff, Rauh and Schlieder (1995) distinguished between the conceptual and inferential cognitive adequacy of Allen's interval calculus. The former refers to the thirteen base relations as a representational system and the latter to the compositions of these relations as a tool for reasoning. The results of two memory experiments on conceptual adequacy show that people use ordinal information similar to the interval relations when representing and remembering spatial arrangements. Furthermore, symmetry transformations on the interval relations were found to be responsible for most of the errors, whereas conceptualneighborhood theory did not appear to correspond to cognitively relevant concepts. Inferential adequacy was investigated by two reasoning experiments and the results show that in inference tasks where the number of possible interval relations for the composition is more than one, subjects ignore numerous possibilities and interindividually prefer the same relations. Reorientations and transpositions operating on the relations seem to be important for reasoning performance as well, whereas conceptual neighborhood did not appear to affect the difficulty of reasoning tasks based on the interval relations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Allen, J. F. (1983). Maintaining Knowledge about Temporal Intervals, Communications of the ACM 26: 832–843.

    Google Scholar 

  • Aurnague, M. and Vieu, L. (1993). In C. Zelinsky-Wibbelt (ed.), The Semantic of Prepositions - from Mental Processing to Natural Language Processing. Berlin: de Gruyter.

    Google Scholar 

  • Bartlett, J.C., Gernsbacher, M. and Till, R.E. (1987). Remembering Left-right Orientation of Pictures, Journal of Experimental Psychology: Learning, Memory, and Cognition 13: 27–35.

    Google Scholar 

  • Byrne, R. M. J. and Johnson-Laird, P. N. (1989). Spatial Reasoning, Journal of Memory and Language 28: 564–575.

    Google Scholar 

  • Charniak, E. and McDermott, D. (1985). Introduction to Artificial Intelligence. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Cohn, A. G. (1997). Qualitative Spatial Representation and Reasoning Techniques. In KI-97: Advances in Artificial Intelligence (pp. 1–30). Berlin: Springer.

    Google Scholar 

  • Collins, A. and Quillian, M.R. (1969). Retrieval Time from Semantic Memory, Journal of Verbal Learning and Verbal Behavior 8: 240–247.

    Google Scholar 

  • Chang, S. K. and Jungert, E. (1996). Symbolic Projection for Image Information Retrieval and Spatial Reasoning. London: Academic Press.

    Google Scholar 

  • Egenhofer, M. J. (1991). Reasoning about Binary Topological Relations. In Q. Günther and H.J. Schek (eds.), Proceedings of the Second Symposium on Large Scaled Spatial Databases (pp. 143–160). Berlin: Springer.

    Google Scholar 

  • Egenhofer, M. J. and Mark, D. (1995). Naive Geography. In A.U. Frank and W. Kuhn (eds.), Spatial Information Theory. A Theoretical Basis for GIS. Proceedings of COSIT' 95 pp. 1–16. New York: Springer.

    Google Scholar 

  • Evans, J. St. B. T. (1972). On the Problem of Interpreting Reasoning Data: Logical and Psychological Approaches, Cognition 1: 373–384.

    Google Scholar 

  • Evans, J. St. B. T., Newstead, S. T. and Byrne, R. M. J. (1993). Human Reasoning. Hove: Lawrence Erlbaum Associates.

    Google Scholar 

  • Fernyhough, J., Cohn, A. G. and Hogg, D. C. (1997). Event Recognition Using Qualitative Spatial Reasoning on Automatically Generated Spatio-temporal Models from Visual Input. In Proceedings of IJCA197–Workshop on Spatial and Temporal Reasoning.

  • Freksa, C. (1992). Temporal Reasoning Based on Semi-intervals, Artificial Intelligence 54: 199–227.

    Google Scholar 

  • Freksa, C. (1991). Qualitative Spatial Reasoning. In D. M. Mark and A. U. Frank (eds.), Cognitive and Linguistic Aspects of Geographic Space (pp. 361-372). Dordrecht: Kluwer Academic Publishers.

    Google Scholar 

  • Güsgen, H. W. (1989). Spatial Reasoning Based on Allen's Temporal Logic (Technical Report ICSI TR-89–049). Berkeley, CA: International Computer Science Institute.

    Google Scholar 

  • Hayes, P. J. (1979). The Naive Physics Manifesto. In D. Michie (ed.), Expert Systems in the Microelectronic Age (pp. 242-27). Edingburgh: Edingburgh University Press.

    Google Scholar 

  • Hernández, D. (1994). Qualitative Representation of Spatial Knowledge. Berlin: Springer-Verlag.

    Google Scholar 

  • Johnson-Laird, P. N. (1972). The Three-term Series Problem, Cognition 1: 58–82.

    Google Scholar 

  • Johnson-Laird, P. N. (1983). Mental Models. Towards a Cognitive Science of Language, Inference, and Consciousness. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Johnson-Laird, P. N. and Byrne, R.M.J. (1991). Deduction. Hove: Lawrence Erlbaum Associates.

    Google Scholar 

  • Knauff, M. (1997). Räumliches Wissen und Gedächtnis [Spatial Knowledge and Memory]. Wiesbaden: Deutscher Universitäts-Verlag.

    Google Scholar 

  • Knauff, M. & Johnson-Laird, P. N. (2000). Visual and Spatial Representations in Spatial Reasoning. In Proceedings of the 22nd Annual Conference of the Cognitive Science Society (pp. 759-765). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Knauff, M., Rauh, R. and Renz, J. (1997). A Cognitive Assessment of Topological Spatial Relations: Results from an Empirical Investigation. In S. C. Hirtle and A. U. Frank (eds.), Spatial Information Theory. A Theoretical Basis for GIS. Proceedings of COSIT 97 (pp. 193–206). New York: Springer.

    Google Scholar 

  • Knauff, M., Rauh, R. and Schlieder, C. (1995). Preferred Mental Models in Qualitative Spatial Reasoning: A Cognitive Assessment of Allen's Calculus. In Proceedings of the Seven-teenth Annual Conference of the Cognitive Science Society (pp. 200–205). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Knauff, M., Rauh, R., Schlieder, C. and Strube, G. (1998). Mental Models in Spatial Reasoning. In C. Freksa, C. Habel and K. F. Wender (eds.), Spatial Cognition - An Inter-disciplinary Approach to Representation and Processing of Spatial Knowledge (Lecture Notes in Computer Science, Vol. 1404, Subseries: Lecture Notes in Artificial Intelligence, pp. 267–291). Berlin: Springer.

    Google Scholar 

  • Levitt, T. and Lawton, D. (1990). Qualitative Navigation for Mobile Robots, Artificial Intelligence 44: 305–360.

    Google Scholar 

  • Ligozat, G. (1990). Weak Representations of Interval Algebras, Proceedings of the Eighth National Conference on Artificial Intelligence (Vol. 2, pp. 715–720). Menlo Park, CA: AAAI Press/MIT Press.

    Google Scholar 

  • Ligozat G. and Bestougeff, H. (1989). On Relations between Intervals, Information Processing Letters 32.

  • McDermott, D. (1992). Spatial Reasoning. In: C. Shapiro (ed.), Encyclopedia of Artificial Intelligence (2nd. ed.) (pp. 1322–1334). New York: John Wiley.

    Google Scholar 

  • Mukerjee, A. and Joe, G. (1990). A Qualitative Model for Space, Proceedings AAAI-90: 721–727.

  • Nebel, B. and Bürckert, H.J. (1995). Reasoning about Temporal Relations: A Maximal Tractable Subclass of Allen's Interval Algebra, Communication of the ACM 42: 43–66.

    Google Scholar 

  • Pribbenow, S. (1993). Räumliche Konzepte in Wissens-und Sprachverarbeitung [Spatial Concepts in Knowledge and Language Processing]. Wiesbaden: Deutscher Universitäts-Verlag.

    Google Scholar 

  • Quillian, M. R. (1968). Semantic Memory. In M. Minsky (ed.), Semantic Information Processing (pp. 227–270). Cambridge, MA: MIT Press.

    Google Scholar 

  • Randell, D.A., Cui, Z. and Cohn, A.G. (1992). A Spatial Logic Based and Regions and Connection. In B. Nebel, W. Swarthout and C. Rich (eds.), Proceedings of the Third Conference on Principles of Knowledge Representation and Reasoning (pp. 165–176). Cambridge, MA: Morgan Kaufmann.

    Google Scholar 

  • Rauh, R., Schlieder, C. and Knauff, M. (1996). —Zur kausalen Wirksamkeit von präferierten mentalen Modellen beim räumlich-relationalen Schließen [The causal power of preferred mental models in spatial-relational reasoning]. Proceedings der zweiten Fachtagung der Gesellschaft für Kognitionswissenschaft. Hamburg: Universität Hamburg, 134–136.

    Google Scholar 

  • Rauh, R. and Schlieder, C. (1997). Symmetries of Model Construction in Spatial Relational Inference. In Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society (pp. 638–643). Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Rips, L. J. (1994). The Psychology of Proof. Cambridge, MA: MIT Press.

    Google Scholar 

  • Schlieder, C. (1995). The Construction of Preferred Mental Models in Reasoning with the Interval Relations (Tech. Rep. 5/95). Freiburg: Institut für Informatik und Gesellschaft der Universität Freiburg (appears also in C. Habel et al. (eds.), Mental Models in Discourse Comprehension and Reasoning).

    Google Scholar 

  • Schlieder, C. (1996). Qualitative Shape Representation. In P.A. Burrough and A.U. Frank (eds.), Geographic Objects with Indeterminate Boundaries (pp. 123–140). London: Taylor &Francis.

    Google Scholar 

  • Schlieder, C. (1998). Diagrammatic Transformation Processes on Two-dimensional Relational Maps. Journal of Visual Languages and Computing 9: 45–59.

    Google Scholar 

  • Strube, G. (1984). Assoziation. Berlin: Springer.

    Google Scholar 

  • Strube, G. (1992). The Role of Cognitive Science in Knowledge Engineering. In F. Schmalhofer, G. Strube and T. Wetter (eds.), Contemporary Knowledge Engineering and Cognition (pp. 161–174). Berlin: Springer.

    Google Scholar 

  • Vilain, M. and Kautz, H. (1986). Constraint Propagation Algorithms for Temporal Reasoning, Proceedings of 5th AAAI: 377–382.

  • Vilain, M., Kautz, H. and van Beek, P. (1990). Constraint Propagation Algorithms for Temporal Reasoning: A Revised Report. In D. S. Weld and J. de Kleer (eds.), Readings in Qualitative Reasoning about Physical Systems. San Mateo, CA: Morgan Kaufmann.

    Google Scholar 

  • Walischewski, H. (1997). Learning and Interpretation of the Layout of Structured Documents. In G. Brewka, C. Habel and B. Nebel (eds.), KI-97 Advances in Artificial Intelligence. Proceedings of the 21st Annual German Conference on Artificial Intelligence (Lecture Notes in Computer Science, Vol. 1303, Subseries: Lecture Notes in Artificial Intelligence, pp. 409–412). Berlin: Springer.

    Google Scholar 

  • Weld, D. S. and De Kleer, J. (eds.) (1990). Readings in Qualitative Reasoning about Physical Systems. San Manteo, CA: Morgan Kaufman.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Knauff, M. The cognitive adequacy of Allen's interval calculus for qualitative spatial representation and reasoning. Spatial Cognition and Computation 1, 261–290 (1999). https://doi.org/10.1023/A:1010097601575

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1010097601575

Navigation