A Linear Estimation-of-Distribution GP System Export

@incollection{citeulike:3452411, abstract = {We present N-gram GP, an estimation of distribution algorithm for the evolution of linear computer programs. The algorithm learns and samples a joint probability distribution of triplets of instructions (or 3-grams) at the same time as it is learning and sampling a program length distribution. We have tested N-gram GP on symbolic regressions problems where the target function is a polynomial of up to degree 12 and lawn-mower problems with lawn sizes of up to 12×12. Results show that the algorithm is effective and scales better on these problems than either linear GP or simple stochastic hill-climbing.}, author = {Poli, Riccardo and Mcphee, Nicholas}, citeulike-article-id = {3452411}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-540-78671-9_18}, doi = {10.1007/978-3-540-78671-9_18}, journal = {Genetic Programming}, keywords = {eda, estimation-of-distribution-algorithm, evolution, evolutionary-computation, genetic-algorithms, genetic-programming, linear-gp, n-gram, n-gram-gp}, pages = {206--217}, posted-at = {2008-10-27 06:01:52}, priority = {0}, title = {A Linear Estimation-of-Distribution GP System}, url = {http://dx.doi.org/10.1007/978-3-540-78671-9_18}, year = {2008} }

TY - CHAP ID - citeulike:3452411 L3 - citeulike-article-id:3452411 N2 - We present N-gram GP, an estimation of distribution algorithm for the evolution of linear computer programs. The algorithm learns and samples a joint probability distribution of triplets of instructions (or 3-grams) at the same time as it is learning and sampling a program length distribution. We have tested N-gram GP on symbolic regressions problems where the target function is a polynomial of up to degree 12 and lawn-mower problems with lawn sizes of up to 12×12. Results show that the algorithm is effective and scales better on these problems than either linear GP or simple stochastic hill-climbing. JF - Genetic Programming EP - 217 TI - A Linear Estimation-of-Distribution GP System SP - 206 KW - eda KW - estimation-of-distribution-algorithm KW - evolution KW - evolutionary-computation KW - genetic-algorithms KW - genetic-programming KW - linear-gp KW - n-gram KW - n-gram-gp AU - Poli, Riccardo AU - Mcphee, Nicholas PY - 2008/// UR - http://dx.doi.org/10.1007/978-3-540-78671-9_18 ER -