New Generation Computing, 23(2005)157-169
Ohmsha, Ltd. and
Springer
Received 20 December 2003
An interactive genetic
algorithm (IGA) provides a means to optimize the input parameters controlling
the behavior of a cellular automaton (CA). The result is one or more combinations
of parameters that allow the CA to reproduce geological patterns of fluid flow
and chemical reactions in fractured media.
Via the IGA, the user can provide
subjective feedback on the quality of the CA results, which would otherwise be
difficult to express numerically. A simple modification to the IGA ranking process,
combined with a self-organizing map, enables the rapid on-line visualization of
the high-dimensional parameter space, and consequent control over the inversion
itself. The insights into the topology of the parameter space offer an understanding
of which parameters control different CA behaviors.
Keywords:Interactive
Evolutionary Computation, Cellular Automata, Self-Organised Maps, Optimisation,
Computer-User Interface.