- author = "Moshe Looks",
- title = "On the behavioral diversity of random programs",
- booktitle = "GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation",
- year = "2007",
- editor = "Dirk Thierens and Hans-Georg Beyer and Josh Bongard and Jurgen Branke and John Andrew Clark and Dave Cliff and Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and Tim Kovacs and Sanjeev Kumar and Julian F. Miller and Jason Moore and Frank Neumann and Martin Pelikan and Riccardo Poli and Kumara Sastry and Kenneth Owen Stanley and Thomas Stutzle and Richard A Watson and Ingo Wegener",
- volume = "2",
- isbn13 = "978-1-59593-697-4",
- pages = "1636--1642",
- address = "London",
-
URL = "
http://gpbib.cs.ucl.ac.uk/gecco2007/docs/p1636.pdf",
-
DOI = "
doi:10.1145/1276958.1277283",
- publisher = "ACM Press",
- publisher_address = "New York, NY, USA",
- month = "7-11 " # jul,
- organisation = "ACM SIGEVO (formerly ISGEC)",
- keywords = "genetic algorithms, genetic programming, empirical Study, heuristics, optimisation, representation",
- abstract = "Generating a random sampling of program trees with specified function and terminal sets is the initial step of many program evolution systems. I present a theoretical and experimental analysis of the expected distribution of uniformly sampled programs, guided by algorithmic information theory. This analysis demonstrates that increasing the sample size is often an inefficient means of increasing the overall diversity of program behaviours (outputs). A novel sampling scheme (semantic sampling) is proposed that exploits semantics to heuristically increase behavioral diversity. An important property of the scheme is that no calls of the problem-specific fitness function are required. Its effectiveness at increasing behavioural diversity is demonstrated empirically for Boolean formulae. Furthermore, it is found to lead to statistically significant improvements in performance for genetic programming on parity and multiplexer problems.",
-
notes = "GECCO-2007 A joint meeting of the sixteenth
international conference on genetic algorithms
(ICGA-2007) and the twelfth annual genetic programming
conference (GP-2007).
ACM Order Number 910071",
