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Spatial Problem Solving in Spatial Structures

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Multi-disciplinary Trends in Artificial Intelligence (MIWAI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10607))

Abstract

The ability to solve spatial tasks is crucial for everyday life and therefore of great importance for cognitive agents. In artificial intelligence (AI) we model this ability by representing spatial configurations and spatial tasks in the form of knowledge about space and time. Augmented by appropriate algorithms, such representations enable the generation of knowledge-based solutions to spatial problems. In comparison, natural embodied and situated cognitive agents often solve spatial tasks without detailed knowledge about underlying geometric and mechanical laws and relationships. They directly relate actions and their effects through physical affordances inherent in their bodies and their environments. Examples are found in everyday reasoning and also in descriptive geometry. In an ongoing research effort we investigate how spatial and temporal structures in the body and the environment can support or even replace reasoning effort in computational processes. We call the direct use of spatial structure Strong Spatial Cognition. Our contribution describes cognitive principles of an extended paradigm of cognitive processing. The work aims (i) to understand the effectiveness and efficiency of natural problem solving approaches; (ii) to overcome the need for detailed representations required in the knowledge-based approach; and (iii) to build computational cognitive systems that make use of these principles.

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Notes

  1. 1.

    http://bscc.spatial-cognition.de.

References

  • Barkowsky, T., Berendt, B., Egner, S., Freksa, C., Krink, T., Röhrig, R., Wulf, A.: The Realator: how to construct reality. In: Rodríguez, R.V. (ed.) ECAI 1994 Workshop W12 Spatial and Temporal Reasoning, Amsterdam (1994)

    Google Scholar 

  • Bateman, J.A., Hois, J., Ross, R., Tenbrink, T.: A linguistic ontology of space for natural language processing. Artif. Intell. 174, 1027–1071 (2010)

    Article  Google Scholar 

  • Braitenberg, V.: Vehicles: Experiments in Synthetic Psychology. MIT Press, Cambridge (1984)

    Google Scholar 

  • Brooks, R.A.: Intelligence without representation. Artif. Intell. 47, 139–159 (1991)

    Article  Google Scholar 

  • Chandrasekaran, B.: Multimodal cognitive architecture: making perception more central to intelligent behavior. In: Proceedings of AAAI, pp. 1508–1512 (2006)

    Google Scholar 

  • Cohn, A.G., Renz, J.: Qualitative spatial representation and reasoning. In: van Harmelen, F., Lifschitz, V., Porter, B. (eds.) Handbook of Knowledge Representation, pp. 551–596. Elsevier, Amsterdam (2008)

    Chapter  Google Scholar 

  • Davis, E., Marcus, G.: Commonsense reasoning and commonsense knowledge in artificial intelligence. CACM 58(9), 92–103 (2015)

    Article  Google Scholar 

  • Modha, D.S., Ananthanarayanan, R., Esser, S.K., Ndirango, A., Sherbondy, A.J., Singh, R.: Cognitive computing. Commun. ACM 54(8), 62–71 (2011)

    Article  Google Scholar 

  • Dreyfus, H., Haugeland, J.: The computer as a mistaken model of the mind. In: Brown, S.C. (ed.) Philosophy of Psychology, pp. 247–258. Palgrave Macmillan, London (1974)

    Chapter  Google Scholar 

  • Dylla, F., Lee, J.H., Mossakowski, T., Schneider, T., van Delden, A., van de Ven, J., Wolter, D.: A survey of qualitative spatial and temporal calculi: algebraic and computational properties. ACM Comput. Surv. (CSUR) 50(1), 7:1–7:39 (2017)

    Article  Google Scholar 

  • Egenhofer, M.J., Franzosa, R.D.: Point-set topological spatial relations. Int. J. Geogr. Inf. Syst. 5(2), 161–174 (1991)

    Article  Google Scholar 

  • Egenhofer, M.J., Mark, D.M.: Modeling conceptual neighborhoods of topological line-region relations. Int. J. Geogr. Inf. Syst. 9(5), 555–565 (1995)

    Article  Google Scholar 

  • Freksa, C.: Conceptual neighborhood and its role in temporal and spatial reasoning. In: Singh, M., Travé-Massuyès, L. (eds.) Decision Support Systems and Qualitative Reasoning, pp. 181–187. North-Holland, Amsterdam (1991a)

    Google Scholar 

  • Freksa, C.: Qualitative spatial reasoning. In: Mark, D.M., Frank, A.U. (eds.) Cognitive and Linguistic Aspects of Geographic Space, pp. 361–372. Kluwer, Dordrecht (1991b)

    Chapter  Google Scholar 

  • Freksa, C.: Spatial computing – how spatial structures replace computational effort. In: Raubal, M., Mark, D., Frank, A. (eds.) Cognitive and Linguistic Aspects of Geographic Space, pp. 23–42. Springer, Heidelberg (2013). doi:10.1007/978-3-642-34359-9_2

    Chapter  Google Scholar 

  • Freksa, C.: Computational problem solving in spatial substrates – a cognitive systems engineering approach. Int. J. Softw. Inf. 9(2), 279–288 (2015a)

    Google Scholar 

  • Freksa, C.: Strong spatial cognition. In: Fabrikant, S.I., Raubal, M., Bertolotto, M., Davies, C., Freundschuh, S., Bell, S. (eds.) COSIT 2015. LNCS, vol. 9368, pp. 65–86. Springer, Cham (2015b). doi:10.1007/978-3-319-23374-1_4

    Chapter  Google Scholar 

  • Freksa, C., Barkowsky, T., Dylla, F., Falomir, Z., Olteteanu, A.-M., van de Ven, J.: Spatial problem solving and cognition. In: Zacks, J., Taylor, H. (eds.) Representations in Mind and World. Routledge, New York (2018)

    Google Scholar 

  • Freksa, C., Olteteanu, A.-M., Ali, A.L., Barkowsky, T., van de Ven, J., Dylla, F., Falomir, Z.: Towards spatial reasoning with strings and pins. In: Advances in Cognitive Systems 4, Poster Collection #22, pp. 1–15 (2016). http://www.cogsys.org/papers/ACS2016/Posters/Freksa_et.al-ACS-2016.pdf

  • Freksa, C., Schultheis, H.: Three ways of using space. In: Montello, D.R., Grossner, K.E., Janelle, D.G. (eds.) Space in Mind: Concepts for Spatial Education, pp. 31–48. MIT Press, Cambridge (2014)

    Google Scholar 

  • Frese, U., Larsson, P., Duckett, T.: A multigrid relaxation algorithm for simultaneous localization and mapping. IEEE Trans. Robot. 21(2), 196–207 (2005)

    Article  Google Scholar 

  • Funt, B.: Problem-solving with diagrammatic representations. Artif. Intell. 13(3), 201–230 (1980)

    Article  Google Scholar 

  • Furbach, U., Furbach, F., Freksa, C.: Relating strong spatial cognition to symbolic problem solving – an example. In: Proceedings of 2nd Workshop on Bridging the Gap Between Human and Automated Reasoning, IJCAI, New York (2016). arXiv:1606.04397v1 [cs.AI]

  • Gibson, J.J.: The Ecological Approach to Visual Perception. Lawrence Erlbaum, New Jersey (1979)

    Google Scholar 

  • Glasgow, J., Narayanan, N.H., Chandrasekaran, B. (eds.): Diagrammatic Reasoning: Cognitive and Computational Perspectives. AAAI Press, Menlo Park (1995)

    Google Scholar 

  • Goel, A.K., Jamnik, M., Narayanan, N.H.: Diagrammatic Representation and Inference. Springer, Berlin (2010). doi:10.1007/978-3-642-14600-8

    Book  MATH  Google Scholar 

  • Goel, A.K., Vattam, S., Wiltgen, B., Helms, M.: Cognitive, collaborative, conceptual and creative – four characteristices of the next generation of knowledge-based CAD systems: a study in biologically inspired design. Comput. Aided Des. 44(10), 879–900 (2012)

    Article  Google Scholar 

  • Gooday, J.M., Cohn, A.G.: Conceptual neighbourhood in temporal and spatial reasoning. In: ECAI 1994, Amsterdam (1994)

    Google Scholar 

  • Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, Cambridge (2016)

    MATH  Google Scholar 

  • Kelly III, J.: Computing, cognition and the future of knowing. IBM Research: Cognitive Computing. IBM Corporation (2015)

    Google Scholar 

  • Kirsh, D.: Embodied cognition and the magical future of interaction design. ACM Trans. Comput.-Hum. Interact. 20(1), 3:1–3:30 (2013)

    Article  Google Scholar 

  • Lakoff, G., Johnson, M.: Metaphors we Live by. University of Chicago Press, Chicago (1980)

    Google Scholar 

  • Larkin, J.H., Simon, H.A.: Why a diagram is (sometimes) worth ten thousand words. Cogn. Sci. 11, 65–99 (1987)

    Article  Google Scholar 

  • Mansouri, M., Pecora, F.: A representation for spatial reasoning in robotic planning. In: International Conference on Intelligent Robots and Systems (IROS) - Workshop on AI-Based Robotics (2013)

    Google Scholar 

  • Marr, D.: Vision. MIT Press, Cambridge (1982)

    Google Scholar 

  • McCarthy, J., Hayes, P.J.: Some philosophical problems from the standpoint of artificial intelligence. Mach. Intell. 4, 463–502 (1969)

    MATH  Google Scholar 

  • Norman, D.A.: The Design of Everyday Things. Basic Books, New York (2013)

    Google Scholar 

  • Pfeifer, R., Scheier, C.: Understanding Intelligence. MIT Press, Cambridge (1999)

    Google Scholar 

  • Polya, G.: How to Solve it. Princeton University Press, Princeton (1956)

    Google Scholar 

  • Raubal, M., Moratz, R.: A functional model for affordance-based agents. In: Rome, E., Hertzberg, J., Dorffner, G. (eds.) Towards Affordance-Based Robot Control. LNCS, vol. 4760, pp. 91–105. Springer, Heidelberg (2008). doi:10.1007/978-3-540-77915-5_7

    Chapter  Google Scholar 

  • Rome, E., Hertzberg, J., Dorffner, G. (eds.): Towards Affordance-Based Robot Control. LNAI, vol. 4760. Springer, Berlin (2008). doi:10.1007/978-3-540-77915-5

    Google Scholar 

  • Sloman, A.: Interactions between philosophy and artificial intelligence: the role of intuition and non-logical reasoning in intelligence. Artif. Intell. 2, 209–225 (1971)

    Article  Google Scholar 

  • Sloman, A.: Afterthoughts on analogical representation. In: Schank, R., Nash-Webber, B. (eds.) Theoretical Issues in Natural Language Processing (TINLAP-1), pp. 431–439 (1975)

    Google Scholar 

  • Sloman, A.: Why we need many knowledge representation formalisms. In: Bramer, M. (ed.) Research and Development in Expert Systems, pp. 163–183. Cambridge University Press, New York (1985)

    Google Scholar 

  • Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. MIT Press, Cambridge (2005)

    MATH  Google Scholar 

  • Vitruvius, M.V.: De Architectura. Book IX, pp. 9–12, text in English, University of Chicago (2017). Accessed 21 Mar 2007

    Google Scholar 

  • Wintermute, S., Laird, J.E.: Bimodal spatial reasoning with continuous motion. In: Proceedings of AAAI, pp. 1331–1337 (2008)

    Google Scholar 

  • Wörgötter, F., Geib, C., Tamosiunaite, M., Aksoy, E.E., Piater, J., Xiong, H., Ude, A., Nemec, B., Kraft, D., Krüger, N., Wächter, M., Asfour, T.: Structural bootstrapping – a novel, generative mechanism for faster and more efficient acquisition of action-knowledge. IEEE Trans. Auton. Mental Dev. 7(2), 140–154 (2015)

    Article  Google Scholar 

  • Wolter, D., Wallgrün, J.O.: Qualitative spatial reasoning for applications: new challenges and the SparQ toolbox. In: Hazarika, S.M. (ed.) Qualitative Spatio-Temporal Representation and Reasoning, pp. 336–362. IGI Global (2012)

    Google Scholar 

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Authors and Affiliations

  1. Bremen Spatial Cognition Center, University of Bremen, Bremen, Germany

    Christian Freksa, Ana-Maria Olteţeanu, Thomas Barkowsky, Jasper van de Ven & Holger Schultheis

Authors
  1. Christian Freksa
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  2. Ana-Maria Olteţeanu
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  3. Thomas Barkowsky
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  4. Jasper van de Ven
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  5. Holger Schultheis
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Correspondence to Christian Freksa .

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Editors and Affiliations

  1. Universiti Teknologi Brunei, Gadong, Brunei Darussalam

    Somnuk Phon-Amnuaisuk

  2. Universiti Teknologi Brunei, Gadong, Brunei Darussalam

    Swee-Peng Ang

  3. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Soo-Young Lee

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Freksa, C., Olteţeanu, AM., Barkowsky, T., van de Ven, J., Schultheis, H. (2017). Spatial Problem Solving in Spatial Structures. In: Phon-Amnuaisuk, S., Ang, SP., Lee, SY. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2017. Lecture Notes in Computer Science(), vol 10607. Springer, Cham. https://doi.org/10.1007/978-3-319-69456-6_2

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