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Advanced Artificial Intelligence Lecture 22: Wong

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Title: Advanced Artificial Intelligence Lecture 22: Wong


1
Advanced Artificial IntelligenceLecture 22
Wong LeungEvolutionary Program Induction
directed by Logic Grammars
  • Bob McKay
  • School of Computer Science and Engineering
  • College of Engineering
  • Seoul National University

2
Outline
  • Logenpro
  • Definite Clause Grammars
  • Grammars for type restrictions
  • Grammars to incorporate syntactic domain
    knowledge
  • Grammars to incorporate semantic domain knowledge?

3
History
  • 1992 Cohen, CFG to control ILP search space
  • 1994/95 - grammars to control GP search space
  • Whigham
  • Wong Leung
  • Geyer-Schulz

4
Why grammars?
  • Language bias
  • Search bias
  • Type constraints
  • Homologous crossover

5
Leung Kwong Sak Wong Man Leung
  • Originally Chinese University of Hong Kong
  • Wong now at Lingnan University
  • Very strong group in evolutionary computation and
    genetic programming
  • Logenpro GP system 1995, led to book in late
    1990s

6
Logenpro
  • Grammar-based genetic programming system
  • Defines a genetic programming system constrained
    by a grammar
  • Like Whigham, evolves derivation trees
  • Main difference definite clause logic grammars
  • A significant extension of context free grammars
  • Secondary difference Lisp
  • Rather than evolving expressions, logenpro
    evolves complete Lisp programs

7
Definite Clause Grammars
  • Context free grammars extended in two ways
  • Any symbol (termnal or non-terminal) may have
    arguments
  • Generally logical variables
  • Additional (logic) clauses may impose semantic
    constraints on variables

8
Definite Clause Grammar Example
  • a-useful-program - first-component(?X), gramm
    ar rule with parameter is-useful(?X, ?Y),
    semantic constraint on parameters second-comp
    onent(?Y). additional grammar rule with
    parameter

9
Boolean Grammar Example
  • start -gt (defun parity (L) ,s-expr(boolean),
    )) . s-expr(BOOLEAN) -gt T .
    s-expr(BOOLEAN) -gt nil . s-expr(BOOLEAN) -gt
    ( , op, s-expr(BOOLEAN), s-expr(BOOLEAN),
    ) . s-expr(BOOLEAN) -gt ( , parity
    ,s-expr(LIST), ) . s-expr(BOOLEAN) -gt ( ,
    first ,s-expr(LIST), ) . s-expr(LIST) -gt
    L . s-expr(LIST) -gt s-expr(SMALLER-LIST).s-
    expr(SMALLER-LIST)-gt ( , rest ,
    s-expr(LIST),). op -gt AND . op -gt OR
    . op -gt NAND . op -gt NOR .

10
Adding Restrictions
  • start -gt (defun parity (L) , (ifnil L T
    ,s-expr(boolean), )) . s-expr(BOOLEAN) -gt
    T . s-expr(BOOLEAN) -gt nil .
    s-expr(BOOLEAN) -gt ( , op, s-expr(BOOLEAN),
    s-expr(BOOLEAN), ) . s-expr(BOOLEAN) -gt (
    , parity , s-expr(SMALLER-LIST), ) .
    s-expr(BOOLEAN) -gt ( , first
    ,s-expr(LIST), ) . s-expr(LIST) -gt L .
    s-expr(LIST) -gt s-expr(SMALLER-LIST).s-expr(SMA
    LLER-LIST)-gt ( , rest , s-expr(LIST),).
    op -gt AND . op -gt OR . op -gt NAND
    . op -gt NOR .

11
Experiments in Paper
  • Even-n-parity for fixed n
  • Even-n-parity general recursive function
  • using highly constrained grammar to limit the
    search space

12
Definite Clause vs Context Free
  • In theory, definite clause grammars significantly
    extend context free grammars
  • Is this important?
  • Almost all applications only use the context-free
    sub-part of definite clause grammars
  • In particular, the experiments in the paper do
    not use the extensions in any important way
  • Everything can be done with context free grammars
  • Is it worth the extra computational cost?

13
Summary
  • Logenpro
  • Definite Clause Grammars
  • Grammars for type restrictions
  • Grammars to incorporate syntactic domain
    knowledge
  • Grammars to incorporate semantic domain knowledge?

14
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