- author = "Michael D. Schmidt and Hod Lipson",
- title = "Predicting solution rank to improve performance",
- booktitle = "GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation",
- year = "2010",
- editor = "Juergen Branke and Martin Pelikan and Enrique Alba and Dirk V. Arnold and Josh Bongard and Anthony Brabazon and Juergen Branke and Martin V. Butz and Jeff Clune and Myra Cohen and Kalyanmoy Deb and Andries P Engelbrecht and Natalio Krasnogor and Julian F. Miller and Michael O'Neill and Kumara Sastry and Dirk Thierens and Jano {van Hemert} and Leonardo Vanneschi and Carsten Witt",
- isbn13 = "978-1-4503-0072-8",
- pages = "949--956",
- keywords = "genetic algorithms, genetic programming, coevolution, symbolic regression",
- month = "7-11 " # jul,
- organisation = "SIGEVO",
- address = "Portland, Oregon, USA",
-
DOI = "
doi:10.1145/1830483.1830652",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- abstract = "Many applications of evolutionary algorithms use fitness approximations, for example coarse-grained simulations in lieu of computationally intensive simulations. Here, we propose that it is better to learn approximations that accurately predict the ranks of individuals rather than explicitly estimating their real-valued fitness values. We present an algorithm that coevolves a rank-predictor which optimises to accurately rank the evolving solution population. We compare this method with a similar algorithm that uses fitness-predictors to approximate real-valued fitnesses. We benchmark the two approaches using thousands of randomly-generated test problems in Symbolic Regression with varying difficulties. The rank prediction method showed a 5-fold reduction in computational effort for similar convergence rates. Rank prediction also produced less bloated solutions than fitness prediction.",
-
notes = "Randomly generated symbolic regression problems.
Co-evolve three populations. Sine Cosine. Bloat
See also \cite{Schmidt:2010:GPTP}. Also known as \cite{1830652} GECCO-2010 A joint meeting of the nineteenth international conference on genetic algorithms (ICGA-2010) and the fifteenth annual genetic programming conference (GP-2010)",
