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A General Approach to Automatic Programming Using Occam's Razor, Compression, and Self-Inspection
Extended Abstract
Peter Galos, Peter Nordin, Joel Olsén, and Kristofer Sundén Ringnér
Complex Systems Group
Department of Physical ResourceTheory
Chalmers University of Technology
S-412 96 Göteborg,Sweden
Abstract. This paper describes a novel general method for automatic programming which can be seen as a generalization of techniques such as genetic programming and ADATE. The approach builds on the assumption that data compression can be used as a metaphor for cognition and intelligence. The proof-of-concept system is evaluated on sequence prediction problems. As a starting point, the process of inferring a general law from a data set is viewed as an attempt to compress the observed data. From an artificial intelligence point of view, compression is a useful way of measuring how deeply the observed data is understood. If the sequence contains redundancy it exists a shorter description i.e. the sequence can be compressed.
LNCS 2724, p. 1806 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003