- author = "Una-May O'Reilly and Franz Oppacher",
- title = "Program Search with a Hierarchical Variable Length Representation: Genetic Programming, Simulated Annealing and Hill Climbing",
- booktitle = "Parallel Problem Solving from Nature -- PPSN III",
- year = "1994",
- editor = "Yuval Davidor and Hans-Paul Schwefel and Reinhard Manner",
- series = "Lecture Notes in Computer Science",
- number = "866",
- pages = "397--406",
- address = "Jerusalem",
- publisher_address = "Berlin, Germany",
- month = "9-14 " # oct,
- publisher = "Springer-Verlag",
- keywords = "genetic algorithms, genetic programming, Simulated Annealing, Search Technique",
- ISBN = "3-540-58484-6",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/ppsn-94.ps.gz",
-
URL = "
http://citeseer.ist.psu.edu/oreilly94program.html",
-
DOI = "
10.1007/3-540-58484-6_283",
- size = "10 pages",
- abstract = "This paper presents a comparison of Genetic Programming(GP) with Simulated Annealing (SA) and Stochastic Iterated Hill Climbing (SIHC) based on a suite of program discovery problems which have been previously tackled only with GP. All three search algorithms employ the hierarchical variable length representation for programs brought into recent prominence with the GP paradigm. We feel it is not intuitively obvious that mutation-based adaptive search can handle program discovery yet, to date, for each GP problem we have tried, SA or SIHC also work.",
-
notes = "PPSN3
A longer version is SFI Technical Report 94-04-021 \cite{OReilly:1994:GPSAHCsfi}",
- size = "10 pages",
