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Insects, Robots

VT. Insects, Robots. Barry Smith http://ifomis.de. The Technological Background. How the world became part of the World Wide Web. the cheese. Sources. “Motion in Databases: Issues and Possible Solutions” Ouri Wolfson (University of Illinois)

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Insects, Robots

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  1. VT

  2. Insects, Robots • Barry Smith • http://ifomis.de

  3. The Technological Background • How the world became part of the World Wide Web the cheese

  4. Sources • “Motion in Databases: Issues and Possible Solutions” • Ouri Wolfson (University of Illinois) • “Intersection of GI and IT Spatial Databases” • Max J. Egenhofer (University of Maine)

  5. Information Technologies • Global Positioning Systems (GPS)

  6. Information Technologies • Digital cameras

  7. Information Technologies • Digital video cameras

  8. Information Technologies • Meteorological sensors • chemical • biological • …wearable computers Microsensors

  9. Location based services Examples: Where is the closest gas station? How do I get there? Track my pet/child/prisoner

  10. Location based services

  11. Location based services Wall Street Journal May 8, 2000: Location-based services a killer application for the wireless internet Strategy Analytics: consumer lbs a $7B market in North America by 2005 Why now? – Proliferation of portable/wearable/wireless devices

  12. Moving Objects Database Technology GPS GPS Wireless link GPS • Query example: • How often is bus #5 late by more than 10 minutes at station 20?

  13. Moving Objects Database Technology GPS GPS Wireless link GPS • Trigger example: • Send message when helicopter is in a given geographic area (trigger)

  14. Moving Objects Database Technology GPS GPS Wireless link GPS • Query example: • List trucks that will reach destination within 20 minutes (future query)

  15. Moving Objects Database Technology GPS GPS Wireless link GPS • Present query: • List taxi cabs within 1 mile of my location

  16. PalmPilot context aware • Display the wiring/plumbing behind this wall • Display seismographic features of a terrain a geologist is viewing • Display vital signs of a patient a doctor is examining

  17. European Media Lab, Heidelberg • Tourism information services • Intelligent, speaking camera plus map display • Display all non-smoking restaurants within walking distance of the castle • Read out a history of the building my camera is pointing to

  18. Mobile e-commerce • Inform a person located at L who needs items of a given sort where he can buy them (a) most quickly (b) most cheaply (c) at 2am. • Inform a person walking past a bar of his buddies in the bar

  19. Further Applications • Digital battlefield • Emergency response • Air traffic control • Supply chain management • Mobile workforce management • Dynamic allocation of bandwidth in cellular network

  20. From Fodor to Gibson

  21. derived intentionality Traditional Syntactic/Semantic Approach to Information Systems 011011101010001000100010010010010010010001001111001001011011110110111011

  22. You can’t get orange juice into the computer • have to use ‘strings’ instead • classes, categories, entities, concepts …

  23. String-Arrays vs. Objects • ghjui123 • xxxxx • xxxxx

  24. Fodor’s Methodological Solipsism 011011101010001000100010010010010010010001001111001001011011110110111011

  25. Humans, Machines, and the Structure of Knowledge • Harry M. Collins • SEHR, 4: 2 (1995)

  26. Knowledge-down-a-wire • Imagine a 5-stone weakling having his brain loaded with the knowledge of a champion tennis player. • He goes to serve in his first match • -- Wham! – • his arm falls off. • He just doesn't have the bone structure or muscular development to serve that hard.

  27. Types of knowledge/ability/skill • those that can be transferred simply by passing signals from one brain/computer to another. • those that can’t:

  28. Sometimes it is the body which knows (the hardware)

  29. Sometimes it is the world which knows

  30. I know where the book is • = I know how to find it • I know what the square root of 2489 is • = I know how to calculate it • I know how to recognize the presence of a tiger • = by smell, noise … (in real-world context)

  31. A. Clark, Being There • humans can accomplish much without building detailed, internal models; we rely on • Epistemic action = • manipulating Scrabble tiles – using the re-arranged pieces as basis for brain's pattern-completing abilities • writing one large number above another to multiply them with pen on paper

  32. A. Clark, Being There • we can rely also on • External scaffolding = maps, models, tools, language, culture • we act so as to simplify cognitive tasks by "leaning on" the structures in our environment.

  33. Not all calculations are done inside the head • Not all thinking is done inside the head

  34. Types of knowledge/ability/skill • those that can be transferred simply by passing signals from one brain/computer to another. • those that can’t: • -- here the "hardware" is important; • abilities/skills contained • (a) in the body • (b) in the world

  35. From • The Methodological Solipsist Approach to Information Processing • To • The Ecological Approach to Information Processing

  36. Fodorian Psychology • To understand human cognition we should study the mind/brain in abstraction from its real-world environment • (as if it were a hermetically sealed Cartesian ego)

  37. Gibsonian Ecological Psychology • To understand human cognition we should study the moving, acting human person as it exists in its real-world environment • and taking account how it has evolved into this real-world environment • We are like tuning forks – tuned to the environment which surrounds us

  38. Fodorian View of Information Systems • To understand information systems we should study their manipulation of syntactic strings

  39. Gibsonian Ecological View of Information Systems • To understand information systems we should study the hardware as it exists embedded in its real-world environment • and taking account the environment for which it was designed and built • Information systems are like tuning forks – they resonate in tune to their surrounding environments

  40. Functioning of Information System intelligible only as part of environment 011011101010001000100010010010010010010001001111001001011011110110111011

  41. The problem of ontology • different groups use incompatible terminologies

  42. Understanding how we can resolve these incompatibilities is a difficult problem whose solution might throw light also on how the human mind copes with large amounts of highly variegated types of data

  43. Consider for example how the human mind • copes with complex phenomena in the social realm (e.g. speech acts of promising) • which involve: • experiences (speaking, perceiving), • intentions, • language, • action, • deontic powers, • background habits, • mental competences, • records and representations

  44. How resolve incompatibilities between the terminologies used by different groups? • “ONTOLOGY” = the solution of first resort • (compare: kicking a television set) • But what does ‘ontology’ mean? • Current most popular answer: a collection of terms and definitions satisfying constraints of description logic

  45. Description logic • a decidable logic • (thus much weaker than first-order predicate logic) • for manipulating hierarchies of terms

  46. Example: The Semantic Web • Vast amount of heterogeneous data sources • Need dramatically better support at the level of metadata • The ability to query and integrate across different conceptual systems: • The currently preferred answer is: The Semantic Web

  47. Tim Berners-Lee, inventor of the internet • ‘sees a more powerful Web emerging, one where documents and data will be annotated with special codes allowing computers to search and analyze the Web automatically. The codes … are designed to add meaning to the global network in ways that make sense to computers’ • and built out of these ingredients: • OWL (Ontology Web Language) • RDF (Resource Descriptor Framework) • DAML (Darpa Agent Mark-up Language) • Washington Post, January 30, 2003

  48. hyperlinked vocabularies, called ‘ontologies’ will be used by Web authors • ‘to explicitly define their words and concepts as they post their stuff online. • ‘The idea is the codes would let software "agents" analyze the Web on our behalf, making smart inferences that go far beyond the simple linguistic analyses performed by today's search engines.’

  49. Practical problems • of the semantic web: • who will police the coding?

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