%0 Conference Paper %1 conf/wilf/FalcoCPT05 %A De Falco, Ivan %A Della Cioppa, Antonio %A Passaro, A. %A Tarantino, Ernesto %B Fuzzy Logic and Applications, 6th International Workshop, WILF 2005, Revised Selected Papers %C Crema, Italy %D 2005 %E Bloch, Isabelle %E Petrosino, Alfredo %E Tettamanzi, Andrea %I Springer %K Solomonoff algorithms, chaotic complexity, genetic programming, series %P 156--163 %R doi:10.1007/11676935_19 %T Genetic Programming for Inductive Inference of Chaotic Series %V 3849 %X In the context of inductive inference Solomonoff complexity plays a key role in correctly predicting the behavior of a given phenomenon. Unfortunately, Solomonoff complexity is not algorithmically computable. This paper deals with a Genetic Programming approach to inductive inference of chaotic series, with reference to Solomonoff complexity, that consists in evolving a population of mathematical expressions looking for the 'optimal' one that generates a given series of chaotic data. Validation is performed on the Logistic, the Henon and the Mackey-Glass series. The results show that the method is effective in obtaining the analytical expression of the first two series, and in achieving a very good approximation and forecasting of the Mackey-Glass series. %@ 3-540-32529-8

@inproceedings{conf/wilf/FalcoCPT05, abstract = {In the context of inductive inference Solomonoff complexity plays a key role in correctly predicting the behavior of a given phenomenon. Unfortunately, Solomonoff complexity is not algorithmically computable. This paper deals with a Genetic Programming approach to inductive inference of chaotic series, with reference to Solomonoff complexity, that consists in evolving a population of mathematical expressions looking for the 'optimal' one that generates a given series of chaotic data. Validation is performed on the Logistic, the Henon and the Mackey-Glass series. The results show that the method is effective in obtaining the analytical expression of the first two series, and in achieving a very good approximation and forecasting of the Mackey-Glass series.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Crema, Italy}, author = {{De Falco}, Ivan and {Della Cioppa}, Antonio and Passaro, A. and Tarantino, Ernesto}, bibdate = {2006-02-22}, bibsource = {DBLP, http://dblp.uni-trier.de/db/conf/wilf/wilf2005.html#FalcoCPT05}, biburl = {https://www.bibsonomy.org/bibtex/21f1aa31306b8e349d1f4cba4f98c1972/brazovayeye}, booktitle = {Fuzzy Logic and Applications, 6th International Workshop, WILF 2005, Revised Selected Papers}, doi = {doi:10.1007/11676935_19}, editor = {Bloch, Isabelle and Petrosino, Alfredo and Tettamanzi, Andrea}, interhash = {a412496fd8c2995522b034416f7ea745}, intrahash = {1f1aa31306b8e349d1f4cba4f98c1972}, isbn = {3-540-32529-8}, keywords = {Solomonoff algorithms, chaotic complexity, genetic programming, series}, month = {September 15-17}, pages = {156--163}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, size = {8 pages}, timestamp = {2008-06-19T17:38:30.000+0200}, title = {Genetic Programming for Inductive Inference of Chaotic Series}, volume = 3849, year = 2005 }