%0 Generic
%A Yu, T
%A Clack, C
%C San Francisco, CA
%D 1998
%F discovery:10087119
%I Morgan Kaufman
%P 416-421
%T PolyGP: a polymorphic genetic programming system in Haskell
%U https://discovery.ucl.ac.uk/id/eprint/10087119/
%X In general, the machine learning  process can be accelerated through the  use of additional knowledge about the  problem solution. For example, monomorphic typed Genetic Programming  (GP) uses type information to reduce the  search space and improve performance.  Unfortunately, monomorphic typed GP  also loses the generality of untyped GP:  the generated programs are only suitable for inputs with the specified type.  Polymorphic typed GP improves over  monomorphic and untyped GP by  allowing the type information to be  expressed in a more generic manner, and  yet still imposes constraints on the  search space. This paper describes a  polymorphic GP system which can generate polymorphic programs: programs  which take inputs of more than one type  and produce outputs of more than one  type.
%Z This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.