Editing Interactive evolutionary computation (section)

==IEC types==

IEC methods include interactive [[evolution strategy]],<ref>Herdy, M. (1997), Evolutionary Optimisation based on Subjective Selection – evolving blends of coffee. Proceedings 5th European Congress on Intelligent Techniques and Soft Computing (EUFIT’97); pp 2010-644.</ref> interactive genetic algorithm,<ref>*Caldwell, C. and Johnston, V.S. (1991), Tracking a Criminal Suspect through "Face-Space" with a Genetic Algorithm, in Proceedings of the Fourth International Conference on Genetic Algorithm, Morgan Kaufmann Publisher, pp.416-421, July 1991</ref><ref>{{cite journal|author=Milani, A.|year=2004|title=Online Genetic Algorithms|journal=International Journal of Information Theories and Applications|volume=11|pages=20–28|url=http://sci-gems.math.bas.bg/jspui/bitstream/10525/838/1/ijita11-1-p04.pdf}}
</ref> interactive [[genetic programming]],<ref>{{cite journal |last=Sims |first=K. |year=1991 |title=Artificial Evolution for Computer Graphics |journal=Computer Graphics |volume=25 |issue=4 |pages=319–328|doi=10.1145/127719.122752 |citeseerx=10.1.1.226.7450 }}</ref><ref>Sims, K. (1991), Interactive Evolution of Dynamical Systems. First European Conference on Artificial Life, MIT Press
</ref><ref>Unemi, T. (2000). SBART 2.4: an IEC tool for creating 2D images, Movies and Collage, Proceedings of 2000 Genetic and Evolutionary Computational Conference workshop program, Las Vegas, Nevada, July 8, 2000, p.153</ref> and [[human-based genetic algorithm]].<ref>{{cite book|author=Kosorukoff, A.|title=2001 IEEE International Conference on Systems, Man and Cybernetics. E-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236) |year=2001|chapter=Human based genetic algorithm|publisher=IEEE Transactions on Systems, Man, and Cybernetics |volume=5|pages=3464–3469|doi=10.1109/ICSMC.2001.972056|isbn=978-0-7803-7087-6|s2cid=13839604}}</ref>

===IGA===

An interactive genetic algorithm (IGA) is defined as a [[genetic algorithm]] that uses human evaluation. These algorithms belong to a more general category of Interactive evolutionary computation. The main application of these techniques include domains where it is hard or impossible to design a computational fitness function, for example, evolving images, music, various artistic designs and forms to fit a user's aesthetic preferences.<ref>{{cite journal | last1= khan | first1= Shahroz | last2 = Gunpinar | first2 = Erkan |last3 = Sener | first3=Bakir | title= GenYacht: An interactive generative design system for computer-aided yacht hull design | journal= Ocean Engineering | volume= 191|pages= 106462 |year=2019|doi= 10.1016/j.oceaneng.2019.106462| s2cid= 204150911 | url= https://strathprints.strath.ac.uk/70007/ }}</ref> Interactive computation methods can use different representations, both linear (as in traditional [[genetic algorithms]]) and tree-like ones (as in [[genetic programming]]).