History
In 1954, GP began with the evolutionary algorithms first used by Nils Aall Barricelli applied to evolutionary simulations. In the 1960s and early 1970s, evolutionary algorithms became widely recognized as optimization methods. Ingo Rechenberg and his group were able to solve complex engineering problems through evolution strategies as documented in his 1971 PhD thesis and the resulting 1973 book. John Holland was highly influential during the 1970s.
In 1964, Lawrence J. Fogel, one of the earliest practitioners of the GP methodology, applied evolutionary algorithms to the problem of discovering finite-state automata. Later GP-related work grew out of the learning classifier system community, which developed sets of sparse rules describing optimal policies for Markov decision processes. The first statement of modern "tree-based" Genetic Programming (that is, procedural languages organized in tree-based structures and operated on by suitably defined GA-operators) was given by Nichael L. Cramer (1985). This work was later greatly expanded by John R. Koza, a main proponent of GP who has pioneered the application of genetic programming in various complex optimization and search problems. Gianna Giavelli, a student of Koza's, later pionered the use of genetic programming as a technique to model DNA expression.
In the 1990s, GP was mainly used to solve relatively simple problems because it is very computationally intensive. Recently GP has produced many novel and outstanding results in areas such as quantum computing, electronic design, game playing, sorting, and searching, due to improvements in GP technology and the exponential growth in CPU power. These results include the replication or development of several post-year-2000 inventions. GP has also been applied to evolvable hardware as well as computer programs.
Developing a theory for GP has been very difficult and so in the 1990s GP was considered a sort of outcast among search techniques. But after a series of breakthroughs in the early 2000s, the theory of GP has had a formidable and rapid development. So much so that it has been possible to build exact probabilistic models of GP (schema theories, Markov chain models and meta-optimization algorithms).
Read more about this topic: Genetic Programming
Famous quotes containing the word history:
“It is the true office of history to represent the events themselves, together with the counsels, and to leave the observations and conclusions thereupon to the liberty and faculty of every mans judgement.”
—Francis Bacon (15611626)
“There is one great fact, characteristic of this our nineteenth century, a fact which no party dares deny. On the one hand, there have started into life industrial and scientific forces which no epoch of former human history had ever suspected. On the other hand, there exist symptoms of decay, far surpassing the horrors recorded of the latter times of the Roman empire. In our days everything seems pregnant with its contrary.”
—Karl Marx (18181883)
“It gives me the greatest pleasure to say, as I do from the bottom of my heart, that never in the history of the country, in any crisis and under any conditions, have our Jewish fellow citizens failed to live up to the highest standards of citizenship and patriotism.”
—William Howard Taft (18571930)