The Evolution of Mental Models
Advances in Genetic Programming, chapter 9, MIT Press, (1994)Abstract
Most interesting problems do not have solutions that
are simple mappings from the inputs to the correct
outputs; some kind of internal state or memory is
needed to operate well or optimally in these domains.
Traditionally, genetic programming has concentrated on
solving problems in the functional/reactive arena. This
may be due in part to the absence of a natural way to
incorporate memory into the paradigm. This chapter
proposes a simple, Turing-complete addition to the
genetic programming paradigm that seamlessly
incorporates the evolution of the effective gathering,
storage, and retrieval of arbitrarily complicated state
information. A new environment is presented and used to
evaluate this addition to the paradigm. Experimental
results show that the effective production and use of
complex memory structures can be evolved and that
functions evolving the intelligent use of state quickly
and permanently displace purely reactive and
non-deterministic functions. These results may aid
future research into the causes and constituents of
mental models and are shown to open the field of
genetic programming to include all learning strategies
that are Turing-possible.
Links and resources
Tags
community
@brazovayeye's tags highlighted