- author = "P. A. Whigham and R. I. McKay",
- title = "Genetic approaches to learning recursive relations",
- booktitle = "Progress in Evolutionary Computation",
- publisher = "Springer-Verlag",
- year = "1995",
- editor = "Xin Yao",
- volume = "956",
- series = "Lecture Notes in Artificial Intelligence",
- pages = "17--27",
- publisher_address = "Heidelberg, Germany",
- keywords = "genetic algorithms, genetic programming, Machine Learning, Inductive Logic Programming",
- isbn13 = "978-3-540-60154-8",
-
URL = "
https://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.74.8561",
-
DOI = "
doi:10.1007/3-540-60154-6_44",
- size = "11 pages",
- abstract = "The genetic programming (GP) paradigm is a new approach to inductively forming programs that describe a particular problem. The use of natural selection based on a fitness function for reproduction of the program population has allowed many problems to be solved that require a non-fixed representation. Issues of typing and language forms within the genetic programming paradigm are discussed. The recursive nature of many geospatial problems leads to a study of learning recursive definitions in a subset of a functional language. The inadequacy of GP to create recursive definitions is argued, and a class of problems hypothesised that are difficult for genetic approaches. Operations from the field of Inductive Logic Programming, such as the V and W operators, are shown to have analogies with GP crossover but are able to handle some recursive definitions. Applying a genetic approach to ILP operators is proposed as one approach to learning recursive relations.",
-
notes = "
p18 'the negative results...suggest that GP is _not_ suitable for discovering recursive definitions'. Tries ILP+GP. Tries to learn LISP member function with CAR, CDR, EQ, ATOM, MEMBER.Stack limit of 40 calls was imposed. No solutions found (without ILP), due to fitness function and halting problem? RLGG.",
- affiliation = "University College, University of New South Wales Australian Defence Force Academy Department of Computer Science 2600 Canberra ACT Australia 2600 Canberra ACT Australia",
