Abstract
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.
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