1. Lecture 8-2CS250: Intro to AI/Lisp What do you mean, “What do I mean?” Lecture 8-2 November 18 th, 1999 CS250

2. Lecture 8-2CS250: Intro to AI/Lisp Project comments Need copy-editing Style –Page numbers, citations Code printouts –No crazy wrapping Philosophy projects

3. Lecture 8-2CS250: Intro to AI/Lisp Ontolingua Stanford ontology server –Suite of ontology authoring tools –Library of modular reusable ontologies

4. Lecture 8-2CS250: Intro to AI/Lisp How do we build an ontology? Knowledge engineering Knowledge acquisition Ontological engineering

5. Lecture 8-2CS250: Intro to AI/Lisp Representing U of C What kinds of questions might we want to ask of our knowledge base?

6. Lecture 8-2CS250: Intro to AI/Lisp Steps in Building Decide what to talk about Decide on a vocabulary Encode general rules Encode an instance Pose queries

7. Lecture 8-2CS250: Intro to AI/Lisp What do we get from logic? Logics consist of: –Syntax –Semantics –Proof theory Expressive, but doesn’t say what to express

8. Lecture 8-2CS250: Intro to AI/Lisp A Few Terms Knowledge engineering - Art & science of transforming worldly knowledge into computer reasonable form Knowledge acquisition - Squeezing knowledge from the heads of experts

9. Lecture 8-2CS250: Intro to AI/Lisp Declarative Approach Rides Again Write down what you know, and let the system figure out the rest Separate inferencing from representation –Design an inferencing engine that works with many representations –Free to focus on the best representation

10. Lecture 8-2CS250: Intro to AI/Lisp Good Qualities for a Knowledge Base Clarity Coherence Extensibility Avoid favoring encodings Minimal ontological commitment From “Toward Principles for the Design of Ontologies Used for Knowledge Sharing”“Toward Principles for the Design of Ontologies Used for Knowledge Sharing”

11. Lecture 8-2CS250: Intro to AI/Lisp KE Questions For every sentence added to the knowledge base: –Why is this true? Can its truth be decomposed? –Is it widely applicable? Can I broaden this observation? –Do I need a predicate to denote this class of objects? How does the class relate to other classes? Subclasses? Other class properties?

12. Lecture 8-2CS250: Intro to AI/Lisp KE Strategy  Decide what to talk about –What to focus on, what to ignore  Vocabulary of predicates, functions & constants  Encode general domain knowledge  Encode a specific problem instance  Sit back and ask questions

13. Lecture 8-2CS250: Intro to AI/Lisp 1-Bit Adder 1 2 3 2 1

14. Lecture 8-2CS250: Intro to AI/Lisp What are We Talking About Some concepts we’ll need –Wires as connectors –Gates (AND, OR, XOR & NOT) –Inputs –Outputs What don’t we need? Latency, layout, CMOS, time

15. Lecture 8-2CS250: Intro to AI/Lisp Representing Stuff Distinguish gates from one another –Constants Gate types –Type functions > Type(X1) = XOR Terminals –Output terminal function: Out(1, X1) Connectivity

16. Lecture 8-2CS250: Intro to AI/Lisp Encode General Rules If two terminals are connected, they have the same signal The signal at every terminal is either on or off (but not both) An XOR gate is on iff its inputs are different  t1,t2 Connected(t1,t2)  Signal(t1)=Signal(t2)  t Signal(t)=On  Signal(t)=Off On  Off  g Type(g)=XOR  Signal(Out(1,g)=On  Signal(In(1,g))  Signal(In(2,g))

17. Lecture 8-2CS250: Intro to AI/Lisp Encode Specific Instance Encode the circuit –Gate info –Connections among gates

18. Lecture 8-2CS250: Intro to AI/Lisp Ask the $64,000 Question When will the first output of C1 be off and the second output of C1 to be on? Is the circuit correct? –What are the possible sets of values of all the terminals for the adder circuit?  i1,i2,o1,o2 Signal(In(1,C1))=i1  Signal(In(2,C1))=i2  Signal(In(3,C1))=i3  Signal(Out(1,C1))=o1  Signal(Out(2,C1))=o2

19. Lecture 8-2CS250: Intro to AI/Lisp Other KR’s Case-based reasoning Bayesian networks Neural networks

20. Lecture 8-2CS250: Intro to AI/Lisp Representational Adequacy Metaphysical adequacy Could the world have the representational form suggested without a contradicting the facts of the aspect of the reality we’re interested in? Epistemological adequacy Express facts about the world in a practical way Heuristic adequacy Are the reasoning processes used in solving a problem expressible?

21. Lecture 8-2CS250: Intro to AI/Lisp General Ontologies Categories Measures Composite Objects Time, Space and Change Events and Processes Physical Objects Substances Mental Objects and Beliefs

22. Lecture 8-2CS250: Intro to AI/Lisp Categories Reification –How many people live on Earth? Inheritance Creating taxonomies –Kentucky Fried Chicken –Dewey decimal –LoC –MeSh

23. Lecture 8-2CS250: Intro to AI/Lisp Measures Examples: Height, mass, cost Measure = Units function + a Number

24. Lecture 8-2CS250: Intro to AI/Lisp Composite Objects Not inheritance –Difference between subclass and member Schema Script

25. Lecture 8-2CS250: Intro to AI/Lisp Composite Objects Not inheritance –Difference between subclass and member General event descriptions –Schema –Script

26. Lecture 8-2CS250: Intro to AI/Lisp Using Events to Represent Change What’s the problem? –Continuous time –Multiple agents –Actions of different durations Event calculus - Reify events

27. Lecture 8-2CS250: Intro to AI/Lisp Event Calculus Vocabulary Events are splotches in the space-time continuum Events have subevents Some events are intervals

28. Lecture 8-2CS250: Intro to AI/Lisp Examples Suppose we wish to represent facts about market manias  f f  BulbEating  SubEvent(f,TulipMania)  PartOf(Location(f), Holland)  s s  StockFrenzy  SubEvent(s,USBullMarket)  PartOf(Location(f), ??)  s s  StockFrenzy  SubEvent(s,USBullMarket)  TradedOn(Exchange(s), NASDAQ)

29. Lecture 8-2CS250: Intro to AI/Lisp Place How are places like intervals? Relation In holds among places Location function: Maps an object to the smallest place that contains it

30. Lecture 8-2CS250: Intro to AI/Lisp Processes Why do we need processes when we have events? How can we say: –Barry Sonnenfeld was flying some time yesterday –Barry was flying all day yesterday Kurt D. Fenstermacher: Sonnenfeld directed: Men in Black (1997) Get Shorty (1995) The Addams Family (1991) Kurt D. Fenstermacher: Sonnenfeld directed: Men in Black (1997) Get Shorty (1995) The Addams Family (1991) E(Flying(Barry), Yesterday) T(Flying(Barry), Yesterday)

31. Lecture 8-2CS250: Intro to AI/Lisp A Logical Blender Suppose Bill is accused of killing a zucchini, and when the cold, but efficient, Detective Frigerator (known to his pals as simply “Re”) questions the orange juice pitcher in FOPL, the orange juice has no idea how to say: “Bill was in the kitchen with the tomato all day yesterday”

32. Lecture 8-2CS250: Intro to AI/Lisp Composite Events Use And to combine two events with the usual semantics: And isn’t so bad, but disjunction is a bit more complicated -- how do we say: “I saw the whole thing, the beef or the broccoli stabbed the zucchini all afternoon.”  p,q,e T(And(p, q), e)  T(p, e)  T(q, e)

33. Lecture 8-2CS250: Intro to AI/Lisp Time & Intervals Time is pretty important –Divvy up time into: Moments and ExtendedIntervals –Define a couple handy functions Start End Time Date

34. Lecture 8-2CS250: Intro to AI/Lisp When Intervals Get Together Meet Before After During Overlap

35. Lecture 8-2CS250: Intro to AI/Lisp Objects in the Space-Time Continuum Remember that events are splotches of space-time Some events have coherence through time Need to capture the idea of an object existing through time

36. Lecture 8-2CS250: Intro to AI/Lisp Roman Empire Roman Empire spread across much of Eurasia, expanding and contracting, from 753 B.C. until the 5th century A.D.

37. Lecture 8-2CS250: Intro to AI/Lisp Roman Empire at 218 B.C.

38. Lecture 8-2CS250: Intro to AI/Lisp Roman Empire at 117 A.D.

39. Lecture 8-2CS250: Intro to AI/Lisp Roman Empire at 395 A.D.

40. Lecture 8-2CS250: Intro to AI/Lisp Fluents Roman Empire is an event –Subevents include First, Second and Third Punic Wars One of the first known hammer and anvil movements in battle (216 BC @ Cannae) A fluent allows us to capture the notion of the Roman Empire throughout time T(Male(Emperor(RomanEmpire)), 1stCenturyAD) T(In(Gaul, Roman Empire), AD12)

41. Lecture 8-2CS250: Intro to AI/Lisp Fluent Flavors Fluent is a function, f:Situations Fvalues –Domain is the set of all situations (states of the world) If Fvalues is {TRUE, FALSE} then it’s a Propositional fluent If Fvalues is {All situations} then it’s a Situational fluent

42. Lecture 8-2CS250: Intro to AI/Lisp Substances Less vs. fewer Intrinsic vs. extrinsic properties Substances are those things that are fungible

43. Lecture 8-2CS250: Intro to AI/Lisp Going, Like, Totally Mental What are other agents know, and what are they thinking? –“Everybody’s looking at me” –“They’re trying to kill me” –“You look like someone who knows where I can find extra virgin olive oil” Start with a Believes predicate Believes(Agent, x)

44. Lecture 8-2CS250: Intro to AI/Lisp Reification & You A good first pass: Treat Flies(Superman) as a propositional fluent –Relationships like Believes, Know and When between agents and propositions are propositional attitudes The problem: Can Clark fly? Believes(Agent, Flies(Superman))

45. Lecture 8-2CS250: Intro to AI/Lisp “It is clear.” Referential transparency –Any term can be substituted for an equal term –FOL is referentially transparent

46. Lecture 8-2CS250: Intro to AI/Lisp Knowing for Action Knowing preconditions: What do you need to know to do action a? Knowledge effects: What effect does performing action a have on an agent’s knowledge?

47. Lecture 8-2CS250: Intro to AI/Lisp Replacing that Zucchini Grocery shopping –Percepts –Actions –Goals –Environment