Common-Sense Knowledge of Space: Learning from Experience

Kuipers, Benjamin

Common-Sense Knowledge of Space: Learning from Experience

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Proceedings of the Sixth International Joint Conference 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.

Benjamin Kuipers. 1979. Common-Sense Knowledge of Space: Learning from Experience. In Proceedings of the Sixth International Joint Conference on Artificial Intelligence, IJCAI-79. IJCAI, https://ijcai.org/proceedings/1979/111

@inproceedings{ijcai1979p111,
  title     = {Common-Sense Knowledge of Space: Learning from Experience},
  author    = {Kuipers, Benjamin},
  booktitle = {Proceedings of the Sixth International Joint Conference on
               Artificial Intelligence, {IJCAI-79}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Bruce G. Buchanan},
  year      = {1979},
  month     = {8},
  url       = {https://ijcai.org/proceedings/1979/111},
}

TY  - CPAPER
TI  - Common-Sense Knowledge of Space: Learning from Experience
AU  - Kuipers, Benjamin
T2  - Proceedings of the Sixth International Joint Conference on Artificial Intelligence, IJCAI-79
PB  - International Joint Conferences on Artificial Intelligence
PY  - 1979
UR  - https://ijcai.org/proceedings/1979/111
ER  -