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Gptp 2014 way of the combinator

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Gptp 2014 way of the combinator

  1. 1. THE WAY OFTHE COMBINATOR Bill Worzel billwzel@gmail.com Evolution Enterprises http://evolver.biz GPTheory and Practice 08 May 2014 Ann Arbor, MI
  2. 2. THE SKGP • 15 years ago we developed what was then a novel approach to GP using combinators • Strongly typed, efficient, powerful, reusable code • Algorithm can become superlinear in parallel application because of code reuse
  3. 3. COMBINATORS • Applicative algebra, derived from Lambda calculus, binds left-to-right • Sxyz -> xz(yz) • Kxy -> x • Ix -> x • Bxyz -> x(yz) • Cxyz -> xzy • Yx -> x(Yx)Combinators Functions Quickly
  4. 4. VARIABLE ABSTRACTION • D.A.Turner showed that removing bound variables using combinators could produce an efficient computing system (Turner 1979, A New Implementation Technique for Applicative Languages, Software–Practice and Experience, vol 9, 31-49 ) • Essentially this used the fact we can create expressions that are variable free using combinators to create a highly efficient computer system (Clarke 1980)
  5. 5. THE SKGP • Implements programs as graphs using combinators with GP to produce pure functional (combinator) expressions • Uses strong typing similar to (Yu 1997, 1998)
  6. 6. EVALUATING COMBINATOR EXPRESSION Example: ‘S(S(K +)(K 1))I’ is a curried function that adds 1 to what it is applied to so S(S(K +)(K 1)I applied to 3 is: S(S(K +)(K 1))I 3 S(K +)(K 1)3(I 3) K+3((K 1)3)(I 3) +K 1 3 (I 3) + 1 (I 3) + 1 3 4
  7. 7. COMBINATORS FUNCTIONS QUICKLY BECOME COMPLEX Here is the function for factorial: def fac = S(S(S(K cond)(S(S(K =)(K 0)))I))(K 1))(S(S(K *)I) (S(K fac)(S(S(K -)I)(K 1)))) Evaluation is left as an “exercise to the reader.”
  8. 8. COMBINATOR GRAPHS • Combinator expressions represented as graphs • + 1 2 • fxyz • Sfgx -> fx(gx)
  9. 9. TYPING GP • The SKGP is strongly typed so that it is always “type coherent” • Based on Hindley/Milner type system as described in (Yu 1997) but for combinators instead of lambda expressions • Type is checked during graph creation and resolved at time of mutation and crossover - static typing • If cannot resolve type, back out and try again by creating a new subtree • Strongly typed system will always terminate with same type (halting problem?)
  10. 10. ESCAPINGTHE BOTTLE • (Daida 2003) describes limitation of standard GP in how trees grow • Presents evidence that GP can be limited in its search ability without structure altering operators • Combinators have the property of being ‘structure altering operators’ Daida, unpublished based on Daida 2004 Demonstrating Constraints to Diversity with a Tunably Difficulty Problem for Genetic Programming
  11. 11. CHURCH-ROSSERTHEOREM • The Church-RosserTheorem says pure function evaluation can be order independent: Regardless of order of evaluation, result will be the same • Because of this, each functional piece, when evaluated, can be stored for re-use since order of evaluation does not matter • Normally this is inefficient since some pieces are not used • Because GP shares pieces across generations, reuse gives super-linear speed up: you don’t have to recompute each component
  12. 12. REAL WORLD GP USING SKGP • (Briggs 2006) shows such a system benchmarks well (regression, parity, stack & queue evolution) • What about real world problems? • Process control program for manufacturing process • Modeling chemical kinetics for NASA • Bladder cancer analysis differentiating nodal metastatic cancer from non-metastatic cancer • Colon cancer prognostic
  13. 13. FUTURE DIRECTIONS • Reuse of combinator expressions across generations via caching mechanism • Solving the ‘Y problem’ • Adding chromosome structure

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