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Tony Cohn

Presentation to Networking Geospatial Information Technology for Interoperability and Spatial Ontology School of Computing University of Leeds. Tony Cohn. My/Leeds interests. Knowledge representation and reasoning Qualitative and “common sense” reasoning

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Tony Cohn

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  1. Presentation to Networking Geospatial Information Technology for Interoperability and Spatial OntologySchool of ComputingUniversity of Leeds Tony Cohn

  2. My/Leeds interests • Knowledge representation and reasoning • Qualitative and “common sense” reasoning • Qualitative spatial and spatio-temporal representation and reasoning • Spatial ontologies • Vagueness, uncertainty, granularity • Applications • Cognitive Vision • Mapping the Underworld”

  3. Qualitative Spatial Reasoning • Motivation • Efficiency • Cognitive arguments • Abstraction • Applications (GIS, Vision, Natural Language,…) • Challenge • Expressive and efficient • Expressive calculi • Mereotopology, geometry, orientation • Efficient reasoning • Propositional (modal, intuitionistic, constraint)

  4. E.g. RCC-8 (cf Egenhofer) • 8 provably jointly exhaustive pairwise disjoint relations (JEPD) DC EC PO TPP NTPP EQ TPPi NTPPi Implemented in: CYC, Foundational Anatomy,…

  5. Reasoning Techniques • Tension between expressivity and efficiency • E.g. First order logic formulation of mereotopology is not decidable • Dispense with full first order theory and find decidable subset, e.g. constraint language of RCC8 • In fact, constraint language of RCC8 is tractable • Various tractable disjunctive languages • Variety of special purpose reasoning techniques, e.g.: • Composition tables • Spatial logics

  6. Existential import of Composition Tables Weak reading: 8 x,y,z [[R1(x,y) Æ R2(y,z)] ! [R31(x,z) Ç … Ç R3n(x,z)]] or (extensional reading): 8 x,z [9y[R1(x,y) Æ R2(y,z)] $ [R31(x,z) Ç … Ç R3n(x,z)]] • E.g. consider the TPP x TPP entry 8 x,z [9y[TPP(x,y) Æ TPP(y,z)] $ [TPP(x,z) Ç NTPP(x,z)]] Ã

  7. Qualitative shape • Beyond mereotopology • Orientation calculi • Convexity: conv(x) (+RCC) • Affine geometry

  8. RBG: Region Based Calculus • Primitives: P(x,y), CG(x,y)/Sphere(x) • Categorical • Complete geometry with coordinates • Constraint sublanguages: • MC6: CG, CGTPP, CGNTPP, CNO • RCC8+MC6+relative size • Important research direction: combining calculi

  9. Continuity Networks/Conceptual Neighbourhoods • What are next qualitative relations if entities transform/translate continuously? • E.g. RCC-8 • Basis of qualitative simulator

  10. Space time and continuity • 4D spatio temporal histories • Mereotopological theory • Definition of continuity • Continuous histories • Allows proof of non existence of missing links in conceptual neighbourhood diagram • E.g. DC – PO is impossible

  11. Continuity of Multiple Component Histories • Allowing multiple component histories gives rise to many possible weaker notions of qualitative continuity. • Identity criteria via continuity?

  12. Modal spatio-temporal logics(joint with Zakharyashev et al) Decidable combinations of RCC+temporal logic • PTL (Propositional Temporal Logic) • temporal operators: Since, Until • X Until Y, Z Since W • Can define: • Next: O • Always in the future ¤F (similarly for past) • Sometime in the future ¦F (similarly for past) • Eg ¬ ¤F P(Kosovo,Yugoslavia) • Kosovo will not always be part of Yugoslavia

  13. Extensions • allow the other temporal operators to apply to region variables (iteratively) • E.g. DC(Russia S Russian_empire, Russia S Germany) “The part of Russia that has been Russian since the Russian empire is DC from the part of Germany that became Russian after WW2 (Koenigsberg)” • BRCC8 • can add Boolean operators to region terms and the constraint lanuage of RCC-8 remains decidable (NP complete) • E.g. P(Alps,France+Germany+Italy+Switzerland+Austria)

  14. A Qualitative Representation of Trajectory Pairs • The movement or transition between two objects at an instant can be qualitatively represented using three functions: • movement of the 1st object wrt the 2nd object’s position • movement of the 2nd object wrt the 1st object’s position • relative speed of the 1st object wrt the 2nd object • Since we are interested in a qualitative calculus, we can represent the values of each of these functions by “+”, “0” or “”. • For the first two functions, we take “” to mean motion towards the other object, “+” to mean motion away, and “0” to mean an absence of motion to/from the other object. In the 3rd case, “+/0/ ” mean a greater/same/lower speed respectively. This triple forms the basis of our Qualitative Trajectory Calculus (QTC).

  15. Indeterminate boundaries/vague regions:egg-yolk calculus ... • Using RCC8: 601 jointly exhaustive, pairwise disjoint relations • 40 natural clusters • Can specify that hill and valley are vague regions which touch, without specifying the boundary • Can also be used to represent locational uncertainty as well as boundary indeterminacy • More Leeds work on vagueness (Bennett) • Supervaluation techniques / “in some sense” • Built environment, hydrology ontologies

  16. VISTA & Mapping the Underworld

  17. State of the Art • Each utility has their own asset record • Sometimes digital • Varying degrees of data quality • Often mapped wrt no longer existing reference points • Sensing technology • GPR, “Cat and Genny” • Problems with soil types, dampness, plastic pipes… • Location technology • GNSS, eg GPS • Problem in urban canyons, even with trees in leaf

  18. VISTA Consortium • Stakeholders • Severn Trent Water Thames Water Transport for London • Ordnance Survey Yorks Water BT • United Utils Anglian Water Transco • Three Valleys Water • Contractors and Equipment Manufacturers • Leica Ewan Group Adien • Scott Wilson Jacobs • Umbrella organisations and Professional Bodies • UKWIR (Lead partner) • NJUG Pipeline Industries Guild Inst. Civil Engineers • Universities • Leeds Nottingham • 21 so far and still growing …

  19. A SYSTEM VISION / IDEA ASSET REPAIR & MAINTENANCE Enabling Swift, Safe, Cost Effective Streetworks. RTK GPS OS Maps TPS Sensing and Locating 3G Comms Find it and dig it up 3D GIS data All above Merged into 1 Unit Centrally controlled • Solution Output • 3D Data & Aug Reality • Small • Simple to use • Big buttons • Highly accurate • Real-time Data capture & supply Web Service GML / VRML Data Server

  20. Some Research Challenges • Virtual integration of disparate asset records • Varying data quality • Varying spatial alignment • spatial and non spatial properties: joint ontology • Conversion of legacy raster records • Integration with real-time GNSS data points of street furniture/sensor information • Visualization of integrated information • Taking account of residual uncertainty • Augmented reality?

  21. Cognitive Vision: Two paradigms from 1960’s • Pattern recognition • continuous feature spaces Very successful, huge progress in pattern recognition but relatively little progress on “cognitive vision” • Relational models • qualitative relations between image regions (e.g. touching, part of,inside, near, approaching) • graph matching, symbolic reasoning Potentially useful, but too little interaction/integration with pattern recognition/quantitive approaches • The Challenge: integration

  22. approach • Integration of quantitative and qualitative modes of representation, learning and reasoning: • quantitative visual processing for tracking & motion analysis • qualitative spatio-temporal representations abstract away: • from unnecessary details • error and uncertainty • commonsense knowledge as constraints on interpretations • Learn as much as possible • Autonomously (unsupervised) • Point and learn – any scene!

  23. (Some) Research Issues • What background theory and how to learn it? • How to integrate low level (quantitative) reasoning/representations with higher level symbolic (qualitative)? • How to select preferred abduced explanations of sensor input? • What qualitative representations? • Dealing with noise. • …

  24. Progress to date • System which learned traffic behaviours • Qualitative spatio-temporal models • Learning of qualitative spatial relationships • Allows domain specific distinctions to be learned • Reasoning about classification • Reasoning about commonsense knowledge of continuity to refine ambiguous classifications • Learning symbolic descriptions of intentional behaviours • Use ILP to induce rules to describe simple games • … learning the ontology of the game…

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