A Genetic Programming Approach to Solomonoff’s Probabilistic Induction (Articolo in rivista)

Type
Label
  • A Genetic Programming Approach to Solomonoff’s Probabilistic Induction (Articolo in rivista) (literal)
Anno
  • 2006-01-01T00:00:00+01:00 (literal)
Alternative label
  • De Falco Ivanoe, Tarantino Ernesto, Della Cioppa Antonio, Maisto Domenico (2006)
    A Genetic Programming Approach to Solomonoff’s Probabilistic Induction
    in Lecture notes in computer science
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • De Falco Ivanoe, Tarantino Ernesto, Della Cioppa Antonio, Maisto Domenico (literal)
Pagina inizio
  • 593 (literal)
Pagina fine
  • 602 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 1-1 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • in fase di pubblicazione (literal)
Note
  • ISI Web of Science (WOS) (literal)
Titolo
  • A Genetic Programming Approach to Solomonoff’s Probabilistic Induction (literal)
Abstract
  • In the context of Solomonoff’s Inductive Inference theory, Induction operator plays a key role in modeling and correctly predicting the behavior of a given phenomenon. Unfortunately, this operator is not algorithmically computable. The present paper deals with a Genetic Programming approach to Inductive Inference, with reference to Solomonoff’s algorithmic probability theory, that consists in evolving a population of mathematical expressions looking for the ‘optimal’ one that generates a collection of data and has a maximal a priori probability. Validation is performed on Coulomb’s Law, on the Henon series and on the Arosa Ozone time series. The results show that the method is effective in obtaining the analytical expression of the first two problems, and in achieving a very good approximation and forecasting of the third. (literal)
Prodotto di

Incoming links:


Prodotto
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi
data.CNR.it