Proceedings

Common-Sense Knowledge of Space: Learning from Experience

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Proceedings of the Sixth International Joint Conference on Artificial Intelligence. .

© 1979 International Joint Conferences on Artificial Intelligence

Abstract

The TOUR model is a computational model of human commonsense knowledge of large-scale space. It shows how ob sN \' alions arc assimilated into a description, from multiple perspectives, of the spatial environment. In this paper we propose a representation for sensory events at a level suited to this investigation, and an inference s trategy by which the se ~en s ory events are assimilated into descriptions of spatial structure. We al so di sc u~. s the stales of partial knowledge that occur during the learning process, and show that the represenl<~llon exh t h•l ~ graceful degradatton of performance under resource limitations.

  1. Kuipers, B. J. Rcprescntine Knowledge of Large-Scale Space. MIT Artificial Intelligence Laboratory TR-418, 1977. (Doctoral dissertation, Department of Mathematics, MIT).
  2. Kuipers, B. J. "Modelling spatial knowledge." Cognitive Science 2:2 ( 1978) 129-I 53.
  3. Kuipers, B. J. •o•n representing commonsense knowledge." In N. V. Findler (Ed . ), Associative Nelworl<s---The Representation and Use of Knowledge by Computers. New York: Academic Press, I 979.
  4. Kuipers, B. J. "Commonsense Knowledge of Space: Learning from E~perience." Tufts University Cognitive Science Working Paper I, 1979. (An expanded version of this paper.)
  5. Lynch, K. Tl!e Image of the City. Cambridge, MA: MIT Press, 1960.
  6. Marr, D. "Early processing of visual information." Phil. Trans. Roy. Soc. Lon. B 275(942): (1976) 483-524. (Also MIT AI Memo 340.)
  7. McCarthy, J. "Programs with common sense." In M Minsky <Ed.), Semantic Information Processing. Cambridge, MA: MIT Press, 1968.
  8. Norman, D. A. and Bobrow, D. G. "On data-limited and resource-limited processes." Cognitive Psycholoey 7 (1975) 44-64.

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