Artificial Intelligence, Ontologies, and Common Sense

1. Artificial Intelligence, Ontologies, and Common Sense Ray Larson & Warren Sack University of California, Berkeley School of Information Management and Systems SIMS 202: Information Organization and Retrieval Lecture author: Warren Sack IS202: Information Organization and Retrieval

2. Last Time • Metadata is: • “data about data” (database systems) • Information about Information • Structures and Languages for the Description of Information Resources and their elements (components or features) • “Metadata is information on the organization of the data, the various data domains, and the relationship between them” (Baeza-Yates p. 142) IS202: Information Organization and Retrieval

3. Examples of Metadata • Bibliographic Metadata (traditional Library cataloging) • Dublin Core IS202: Information Organization and Retrieval

4. Today • What is Cognitive Science? • What is Artificial Intelligence? • Knowledge Representation • Languages • Representing Common Sense • Common Sense Interfaces • Story Understanding, Story Generation, and Common Sense IS202: Information Organization and Retrieval

5. Cognitive Science/The Next Four Lectures • 10/30/01 – AI, knowledge representation and common sense • 11/01/01 – Computational Linguistics, Cognitive Psychology and Lexical Knowledge • 11/06/01 – AI and information extraction • 11/08/01 – Linguistics, Philosophy, Psychology, categories, and cognition IS202: Information Organization and Retrieval

6. What is Cognitive Science?Definition by “symptoms” • A definition from Howard Gardner (1986) The Mind’s New Science; the five “symptoms of cognitive science”; the first two are central, the next three are strategic • (1) mental representations • (2) computers • (3) emphasis • (4) epistemology • (5) interdisciplinarity IS202: Information Organization and Retrieval

7. Symptom 1 of Cognitive Science: Mental Representations • To study human cognition it is necessary to posit mental representations and examine those representations separately from the “low level” biological or neurological, on one hand, and also separately from the “high level” social or cultural, on the other hand. (adapted from Gardner, 1986) IS202: Information Organization and Retrieval

8. Symptom 2 of Cognitive Science: Computers • Computers are central to any understanding of the human mind. They are essential both as tools, but also as models of how the mind works. (adapted from Gardner, 1986) IS202: Information Organization and Retrieval

9. Symptom 3 of Cognitive Science:Emphasis • Cognitive scientists deliberately de-emphasis certain factors which may be important for cognitive functioning but whose inclusion would unnecessarily complicate the cognitive-scientific enterprise. These de-emphasized factors include emotional affect, historical, cultural, and other types of context (e.g., issues of embodiment and the senses). (adapted from Gardner, 1986) IS202: Information Organization and Retrieval

10. Symptom 4 of Cognitive Science: Epistemology • Cognitive science is concerned with an area that has historically been a part of philosophy, namely the domain of epistemology. (adapted from Gardner, 1986) IS202: Information Organization and Retrieval

11. Symptom 5 of Cognitive Science: Interdisciplinarity • Cognitive science is an interdisciplinary enterprise. (adapted from Gardner, 1986) IS202: Information Organization and Retrieval

12. The disciplines of cognitive science • Philosophy • Psychology • Artificial Intelligence • Linguistics • Anthropology • Neuroscience IS202: Information Organization and Retrieval

13. The birth of Cognitive Science • Symposium on Information Theory, MIT, 10-12 September 1956 • Allen Newell & Herbert Simon, “Logic Theory Machine” • Noam Chomsky, “Three Models of Language” • George Miller, “The Magical Number Seven” IS202: Information Organization and Retrieval

14. The birth of AI • Rockefeller-sponsored Institute at Dartmouth College, Summer 1956 • John McCarthy, Dartmouth (->MIT->Stanford) • Marvin Minsky, MIT (geometry) • Herbert Simon, CMU (logic) • Allen Newell, CMU (logic) • Arthur Samuel, IBM (checkers) • Alex Bernstein, IBM (chess) • Nathan Rochester, IBM (neural networks) • Etc. IS202: Information Organization and Retrieval

15. Definition of AI “... artificial intelligence [AI] is the science of making machines do things that would require intelligence if done by [humans]” (Minsky, 1963) IS202: Information Organization and Retrieval

16. Some areas of AI • Knowledge Representation • Programming Languages • Natural Language Understanding • Speech Understanding • Vision • Robotics • Planning • Machine Learning • Expert Systems • Qualitative Simulation IS202: Information Organization and Retrieval

17. Common Sense (according to AI) • The advice taker is a proposed program for solving problems by manipulating sentences in formal languages. The main advantages we expect the advice taker to have is that its behavior will be improvable merely by making statements to it, telling it about its symbolic environment and what is wanted from it. To make these statements will require little if any knowledge of the program or the previous knowledge of the advice taker. One will be able to assume that the advice taker will have available to it a fairly wide class of immediate logical consequences of anything it is told and its previous knowledge. This property is expected to have much in common with what makes us describe certain humans as having common sense. We shall therefore say that a program has common sense if it automatically deduces for itself a sufficiently wide class of immediate consequences of anything it is told and what it already knows. John McCarthy, “Programs with Common Sense,” 1959 IS202: Information Organization and Retrieval

18. Common Sense: The original motivation Before describing the advice taker in any detail, I would like to describe more fully our motivation for proceeding in this direction. Our ultimate objective is to make programs that learn from their experience as effectively as humans do. John McCarthy, “Programs with Common Sense,” 1959 IS202: Information Organization and Retrieval

19. Commonsense as Interface • To make our computers easier to use, we must make them more sensitive to our needs. That is, make them understand what we mean when we try to tell them what we want. … If we want our computers to understand us, we’ll need to equip them with adequate knowledge. Marvin Minsky, “Commonsense-based Interfaces,” 2000 IS202: Information Organization and Retrieval

20. What is common sense? Whenever we speak about "commonsense thought," we're referring to things that most people can do, often not even knowing they're doing them. Thus, when you hear a sentence like: "Fred told the waiter he wanted some chips,“ you will infer all sorts of things. Here are just a few of these… • The word "he" means Fred. That is, it's Fred who wants the chips, not the waiter. • This event took place in a restaurant. Fred was a customer dining there at that time. Fred and the waiter were a few feet apart at the time. The waiter was at work there, waiting on Fred at that time. Fred wants potato chips, not wood chips, cow chips, or bone chips. There's no particular set of chips he wants. • Fred wants and expects the waiter to bring him a single portion (1–5 ounces, 5–25 chips) in the next few minutes. Fred will start eating the chips very shortly after he gets them. • Fred accomplishes this by speaking words to the waiter. Fred and the waiter speak the same language. Fred and the waiter are both human beings. Fred is old enough to talk (2+ years of age). The waiter is old enough to work (4+ years, probably 15+). This event took place after the date of invention of potato chips (in 1853). • Fred assumes the waiter also infers all those things. Marvin Minsky, “Commonsense-based Interfaces,” 2000 IS202: Information Organization and Retrieval

21. Can common sense be coded? • www.openmind.org • ThoughtTreasure: www.signiform.com IS202: Information Organization and Retrieval

22. Attempts to code large bodies of knowledge: some previous examples • 18th C.: The French Encyclopediasts: Denis Diderot & Jean D’Alembert size: 20.8 million words, 400,000 unique forms, 18,000 pages of text, 17 volumes of articles, 11 volumes of plate legends, 140 contributors • 19th C.: Thesaurus: Peter Mark Roget size: (third edition) 35,000 synonyms and over 250,000 cross-references • 20th C.: Paul Otlet: Répertoire Bibliographique Universel (RBU) size: (1930) 16 millions entries (authors and subjects) IS202: Information Organization and Retrieval

23. Knowledge Representation In AI, a representation of knowledge is a combination of • data structures and • interpretative procedures that, if used in the right way in a program, will lead to “knowledgeable” behavior. (Barr and Feigenbaum, 1981, p. 143) IS202: Information Organization and Retrieval

24. “Interpretative Procedures” aka Inference • Deduction • Universal instantiation: If something is true of everything, then it is true for any particular thing. • Modus ponens: • Known: (1) the rule if P then Q; and, (2) the fact, P is true; • Infer: Q is true • Abduction • Known: (1) the rule if P then Q; and, (2) the fact, Q is true; • Infer: P is true • Induction: Machine Learning • Known: P(a) is true; P(b) is true; … • Infer: Forall X, P(X) is true IS202: Information Organization and Retrieval

25. Knowledge Representation and Programming Paradigms • Applicative • Functional • Logical • Rule-based • Constraint-based • Object-oriented • Frame-based IS202: Information Organization and Retrieval

26. Applicative define author-of (title) if (title == “Modern Information Retrieval”) then author  [“Baeza-Yates”, “Ribeiro”] IS202: Information Organization and Retrieval

27. Functional define author-of (title) if (title == “Modern Information Retrieval”) then return([“Baeza-Yates”, “Ribeiro”]) else return([]) IS202: Information Organization and Retrieval

28. Logical/Declarative define author-of (“Modern Information Retrieval”, “Baeza-Yates”). define author-of (“Modern Information Retrieval”, “Ribeiro”). define author-of(“The Organization of Information”, “Taylor”). /* backward chaining */ define publication(Author,Title) :- author-of(Title,Author). IS202: Information Organization and Retrieval

29. Rule-Based assert author-of (“Modern Information Retrieval”, “Baeza-Yates”). assert author-of (“Modern Information Retrieval”, “Ribeiro”). assert author-of(“The Organization of Information”, “Taylor”). /* forward chaining */ author-of(Title,Author)  assert publication(Author,Title). IS202: Information Organization and Retrieval

30. Object-oriented define author (Name, Publications) Name isa String Publications isa List define get-publications return Publications /* and/or the other way around */ define publication (Title, Authors) Title isa String Authors isa List define get-author return Authors courseText = new publication(“Modern Information Retrieval”, [“Baeza-Yates”, “Ribeiro”]); IS202: Information Organization and Retrieval

31. Frame-based has-prototype(publications, list) has-prototype(authors,list) has-prototype(inverse,singleton) inverse(inverse,inverse) inverse(authors,publications) has-prototype(Modern-Information-Retrieval, singleton) has-prototype(Baeza-Yates,singleton) has-prototype(Ribeiro,singleton) authors(Modern-Information-Retrieval,Baeza-Yates) authors(Modern-Information-Retrieval,Ribeiro) ? get(ribeiro,publications) IS202: Information Organization and Retrieval

32. Cyc’s top-level Ontology • http://www.cyc.com/cyc-2-1/toc.html IS202: Information Organization and Retrieval

33. Common Sense Knowledge Representation: Examples • Example 1: Story Understanding: SAM, Cullingford et al., 1979 www.sims.berkeley.edu/~sack/Code/Lisp/micro-sam.lisp • Example 2: Story Generation: Talespin, 1976 www.sims.berkeley.edu/~sack/Code/Lisp/micro-talespin.lisp IS202: Information Organization and Retrieval

34. Examples of Talespin’s missing common sense(Meehan, 1976) • Answers to questions can take more than one form. • Don’t always take answers literally. • You can notice things without being told about them. • Gravity is not a living creature. • Stories aren’t really stories if they don’t have a central problem. • Sometimes enough is enough. • Schizophrenia can disfunctional. IS202: Information Organization and Retrieval

35. Next Time • Cognitive Science continued: WordNet IS202: Information Organization and Retrieval