- author = "Brad Alexander and Connie Pyromallis and George Lorenzetti and Brad Zacher",
- title = "Using Scaffolding with Partial Call-Trees to Improve Search",
- booktitle = "14th International Conference on Parallel Problem Solving from Nature",
- year = "2016",
- editor = "Julia Handl and Emma Hart and Peter R. Lewis and Manuel Lopez-Ibanez and Gabriela Ochoa and Ben Paechter",
- volume = "9921",
- series = "LNCS",
- pages = "324--334",
- address = "Edinburgh",
- month = "17-21 " # sep,
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, Grammatical evolution, Recursion",
- isbn13 = "978-3-319-45823-6",
-
DOI = "
doi:10.1007/978-3-319-45823-6_3",
- size = "11 page",
- abstract = "Recursive functions are an attractive target for genetic programming because they can express complex computation compactly. However, the need to simultaneously discover correct recursive and base cases in these functions is a major obstacle in the evolutionary search process. To overcome these obstacles two recent remedies have been proposed. The first is Scaffolding which permits the recursive case of a function to be evaluated independently of the base case. The second is Call- Tree-Guided Genetic Programming (CTGGP) which uses a partial call tree, supplied by the user, to separately evolve the parameter expressions for recursive calls. Used in isolation, both of these approaches have been shown to offer significant advantages in terms of search performance. In this work we investigate the impact of different combinations of these approaches. We find that, on our benchmarks, CTGGP significantly outperforms Scaffolding and that a combination CTGGP and Scaffolding appears to produce further improvements in worst-case performance.",
-
notes = "factorial, odd-evens, log2, Fibonacci and Fibonacci-3,
the nth Lucas number, the nth Pell number.
p331 'We ran our experiments on an AMD Opteron 6348 machine with 48 processors running at 2.8 GHz'
PPSN2016",
