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CIS341 Artificial Intelligence

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Title: CIS341 Artificial Intelligence


1
CIS341 Artificial Intelligence
  • Weeks 8 11
  • Predicate calculus and tableau proofs
  • Natural language syntax and parsing
  • Search and problem solving
  • Parsing as proof, proof as a search problem
  • Coursework 2 proposed dates
  • Given out Friday March 13, due in Friday April
    3rd

2
Week 8 logic and inference revisited
  • Revision of propositional logic
  • Brief overview of proof techniques
  • Introduction to predicate calculus
  • Demonstration of tableau proofs on whiteboard

3
Automated reasoning and formal logic
  • Logic is concerned with validity of inference
  • A central concern of 20th-century mathematical
    logic was to develop systematic, mechanical
    techniques for proving logical consequence
  • The AI subfields of logic programming and
    automated reasoning have built on these efforts
    to develop systems to perform logical inferences.
  • Considerations of speed and efficiency put
    limitations on the kinds of inference that can be
    implemented.

4
Overview of classical logic
  • Just as many people understand the word music to
    refer to European classical music composed
    between the 17th and 20th centuries, so the word
    logic is often shorthand for a variant called
    classical logic.
  • The remainder of these slides provide an overview
    of classical logic, comprising
  • Boolean or propositional logic
  • First-order predicate calculus (the words
    first-order are often omitted)
  • There are many non-classical logics but they do
    not come into this course.

5
Some important terminology
  • A proposition is something that can be true or
    false
  • A proposition is consistent if it is possible for
    it to be true
  • A proposition is inconsistent or contradictory if
    it is not possible for it to be true
  • A proposition is a necessary truth or a tautology
    if it is not possible for it to be false.
  • Class exercise 1 think up examples in each of
    these categories.

6
Boolean or propositional logic
  • Boolean logic is so-called because logical
    formulas are interpreted in terms of Boolean
    truth values
  • True or False
  • T or F
  • 1 or 0
  • The semantics of Boolean logic tells us how to
    calculate the truth values of complex formulas as
    a function of the truth values of their
    constituent literals using truth tables
  • Simple propositions generally written P, Q etc.

7
Syntax of propositional logic
  • Formulas of Boolean logic are made up of
    propositional letters P, Q, R etc and the symbols
  • or ? conjunction, read as and
  • ? inclusive disjunction, read as or
  • ? or negation, read as not
  • ? or ? implication, read as implies or if
    then
  • ? or ? biconditional, read as if and only if
    or iff

8
Truth tables
9
Truth table for
10
Truth table for implication
11
Inference involving implication
  • If the solution is acid, the paper will turn
    red.
  • True ? True the solution is acid, the paper
    turns red. The implication is verified.
  • True ? False the solution is acid, the paper
    does not turn red. The implication is falsified.
  • False ? True the solution is not acid, the paper
    still turns red.
  • False ? False the solution is not acid, the
    paper does not turn red.
  • Is the implication verified or falsified in cases
    3 and 4?

12
Class/self-study exercise 2
  • Construct truth tables for
  • ?P ? Q
  • ?(P Q)
  • ?(P ? Q)
  • ?(P ? Q)

13
Validity of inference
  • An inference is valid if it is not possible for
    the premises to be true and the conclusion false.
  • Valid
  • P, P ?Q / Q
  • ?(P ? Q) / ?P
  • Invalid
  • ?(P Q) / ?P
  • Q, P ?Q / P
  • Validity in propositional logic can be checked
    using truth tables.

14
Some proof techniques
  • Modus ponens
  • P ? Q P / Q
  • Modus tollens
  • P ? Q ?Q / ?P
  • Provide a short cut for calculating inferences
    without constructing truth tables.
  • A proof theory consists of a set of such rules
  • There are proof theories for propositional logic
    which allow all valid inferences to be proved.

15
Resolution rule
  • Equivalent of modus ponens
  • ?P ? Q P / Q
  • Basis of logic programming
  • Requires disjunctions with at most one positive
    literal, for example
  • (P Q) ? R
  • ? (P Q) ? R
  • ?P ? ? Q ? R

16
Tableau proof
  • A graphic proof technique based on tree
    diagrams called semantic tableaux
  • Will be covered in later slides
  • Good tutorial in Wilfred Hodges, Logic
  • Useful online tutorial at http//logic.philosophy.
    ox.ac.uk/main.htm designed for Oxford philosophy
    students
  • Key point there are many proof techniques which
    are all equally sound and complete, i.e. they
    will prove all and only valid arguments.

17
Shortcomings of propositional logic
  • A simple proof
  • Fred is ill.
  • If Fred is ill, he should not drive.
  • So, Fred should not drive.
  • In symbolic form
  • P Fred is ill''
  • Q Fred should not drive
  • Modus ponens
  • P ? Q, P / Q

18
Shortcomings of propositional logic (cont.)
  • So far, so good. But what if Charlie is ill?
  • Do we construct a separate rule for every
    individual?
  • P2 Charlie is ill''
  • Q2 Charlie should not drive
  • P2 ? Q2

19
From propositional logic to predicate calculus
  • Solution is to decompose statements into
    predicates and arguments
  • P(x) x is ill''
  • Q(x) x should not drive
  • P(x) ? Q(x)
  • Proof will look more like this
  • P(x) ? Q(x)
  • P(fred)
  • P(fred) ? Q(fred)
  • ? Q(fred)

20
From propositional logic to predicate calculus
(cont.)
  • Boolean logic is the logic of propositions.
  • Predicate calculus introduces predicates and
    arguments.
  • Arguments can be constant terms or variables.
  • Predicates have to be constant terms in the
    first-order predicate calculus.
  • There are higher-order logics with predicate
    variables but we will not be concerned with them.

21
Quantifiers in predicate calculus I
  • Implicational rules are generally written like
    this
  • ?x(P(x) ? Q(x))
  • The upsidedown A is called the universal
    quantifier this means that the implication is
    true for all values of x (i.e. for any
    individual).
  • Read as for all x, P(x) implies Q(x)
  • Can also be read as all Ps are Q or all Ps Q
  • ?x(fish(x) ? swim(x))
  • ?x(cow(x) ? mammal(x))

22
Quantifiers in predicate calculus II
  • The existential quantifier ? means that statement
    that follows it is true of some individual,
    though we may not know which.
  • ?x(Px Qx)
  • Read as
  • there exists an x such that P(x) and Q(x)
  • some P is a Q
  • some Ps Q
  • ?x(mammal(x) lays-eggs(x))

23
Quantifiers in predicate calculus III
  • You may have noticed that ? generally goes with
    the conjunction and ? goes with the
    implication ?
  • This is very important. What would the following
    mean? Are they true?
  • ?x(fish(x) ? sings(x))
  • ?x(cow(x) mammal(x))
  • This is probably what beginning logic students
    most often get wrong.

24
Quantifiers in predicate calculus IV
  • Multiple quantifiers can be combined in the same
    formula
  • ?x(student(x) ? ?y (tutor(y,x)))
  • Every student has a tutor
  • ?x(professor(x) ??y(course(y) teach(x,y)))
  • There is a professor who does not teach any
    courses

25
Duality of first-order quantifiers
  • The quantifiers ? and ? can be defined in terms
    of each other, using Boolean equivalences
  • ?x(P(x) ? Q(x))
  • ??x?(P(x) ? Q(x))
  • ??x(P(x) ?Q(x))
  • ?x(P(x) Q(x))
  • ??x?(P(x) Q(x))
  • ??x(P(x) ? ?Q(x))
  • Class/self-study exercise 3
  • Convince yourself that the above equivalences are
    correct.

26
Class/self-study exercise 3
  • Convert the following to predicate calculus
  • All mammals are vertebrates.
  • Not all vertebrates are mammals.
  • Only fish swim.
  • Some primates have tails.
  • No primates have feathers.
  • Rhinos eat either leaves or grass.

27
Inference in predicate calculus
  • Techniques such as modus ponens and tableau proof
    are applicable to predicate calculus, with extra
    complications caused by the use of variables.
  • Example given the premises
  • ?x(P(x) ? Q(x))
  • ?y(Q(y) ? R(y))
  • P(fred)
  • we can infer via modus ponens or using tableaux
    (several steps omitted)
  • Q(fred) R(fred)

28
Beginning tableau proofs
  • The Tableau method uses a standard technique of
    proof by contradiction
  • To show whether an argument is valid, attempt to
    show that the premises are inconsistent with the
    negation of the conclusion
  • To show whether a complex proposition is a
    tautology, attempt to show that its negation is
    inconsistent
  • (see whiteboard and handouts)

29
Useful further reading
  • Books
  • A very short introduction to logic, Graham
    Priest, OUP. A clear and stimulating guide to
    basic concepts of logic.
  • Logic, Wilfred Hodges, Penguin. Goes into a lot
    more detail than Priest, useful for
    reference/revision.
  • Website
  • Introduction to logic, http//logic.philosophy.ox.
    ac.uk/main.htm
  • Tutorial on propositional and predicate logic
    aimed at Oxford philosophy students. May not
    display correctly in all browsers. Seems to work
    best in Internet Explorer.
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