A special case of reinforcement learning in which reinforcements are used to increase the proportion of successful functions, they were originated in a 1958 paper in the IBM Journal by R. M. Friedberg, who was trying to change small FORTRAN programs.
John Koza advocated agent representations for them that are limited by representation language syntax. A special case of reinforcement learning in which reinforcements are used to increase the proportion of successful functions, they were originated in a 1958 paper in the IBM Journal by R. M. Friedberg, who was trying to change small FORTRAN programs. Individuals are classically represented in terms of strings over an alphabet, and a fitness function is applied before the population is subjected to random cross-overs and mutations. Described in John Holland's Adaptation in Natural and Artificial Systems, for ten points, name this paradigm of algorithms inspired by evolution.
John Koza advocated agent representations for them that are limited by representation language syntax.
{genetic} algorithms