:Interactive evolutionary computation
Interactive evolutionary computation (IEC) or aesthetic selection is a general term for methods of evolutionary computation that use human evaluation. Usually human evaluation is necessary when the form of fitness function is not known (for example, visual appeal or attractiveness; as in Dawkins, 1986{{cite book|author=Dawkins, R.|title=The Blind Watchmaker|publisher=Longman|year=1986|title-link=The Blind Watchmaker}}) or the result of optimization should fit a particular user preference (for example, taste of coffee or color set of the user interface).
IEC design issues
The number of evaluations that IEC can receive from one human user is limited by user fatigue which was reported by many researchers as a major problem. In addition, human evaluations are slow and expensive as compared to fitness function computation. Hence, one-user IEC methods should be designed to converge using a small number of evaluations, which necessarily implies very small populations. Several methods were proposed by researchers to speed up convergence, like interactive constrain evolutionary search (user intervention) or fitting user preferences using a convex function.{{cite journal|author=Takagi, H.|year=2001|title=Interactive Evolutionary Computation: Fusion of the Capacities of EC Optimization and Human Evaluation|journal=Proceedings of the IEEE |volume=89|issue=9|pages=1275–1296|url=http://www.design.kyushu-u.ac.jp/~takagi/TAKAGI/IECpaper/ProcIEEE_3.pdf|doi=10.1109/5.949485|hdl=2324/1670053|hdl-access=free}} IEC human–computer interfaces should be carefully designed in order to reduce user fatigue. There is also evidence that the addition of computational agents can successfully counteract user fatigue.{{cite journal|author1=Kruse, J. |author2=Connor, A.M.|year=2015|title=Multi-agent evolutionary systems for the generation of complex virtual worlds|journal=EAI Endorsed Transactions on Creative Technologies |volume=15|issue=5|pages=150099|doi=10.4108/eai.20-10-2015.150099|arxiv=1604.05792|s2cid=12670076}}
However IEC implementations that can concurrently accept evaluations from many users overcome the limitations described above. An example of this approach is an interactive media installation by Karl Sims that allows one to accept preferences from many visitors by using floor sensors to evolve attractive 3D animated forms. Some of these multi-user IEC implementations serve as collaboration tools, for example HBGA.
IEC types
IEC methods include interactive evolution strategy,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. interactive genetic algorithm,*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{{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}}
interactive genetic programming,{{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 }}Sims, K. (1991), Interactive Evolution of Dynamical Systems. First European Conference on Artificial Life, MIT Press
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 and human-based genetic algorithm.,{{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}}
=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.{{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/ }} Interactive computation methods can use different representations, both linear (as in traditional genetic algorithms) and tree-like ones (as in genetic programming).
See also
References
{{reflist}}
- Banzhaf, W. (1997), Interactive Evolution, Entry C2.9, in: Handbook of Evolutionary Computation, Oxford University Press, {{ISBN|978-0750308953}}
External links
- {{cite web|url=http://endlessforms.com/|title=EndlessForms.com, Collaborative interactive evolution allowing you to evolve 3D objects and have them 3D printed|access-date=2011-06-18|archive-date=2018-11-14|archive-url=https://web.archive.org/web/20181114121019/http://endlessforms.com/|url-status=dead}}
- {{cite web|url=http://eartweb.vanhemert.co.uk/|title=Art by Evolution on the Web Interactive Art Generator|access-date=2010-04-09|archive-date=2018-04-15|archive-url=https://web.archive.org/web/20180415092047/http://eartweb.vanhemert.co.uk/|url-status=dead}}
- {{cite web|url=http://www.visionmetric.com |title=Facial composite system using interactive genetic algorithms}}
- {{cite web|url=http://www.karlsims.com/galapagos/|title=Galapagos by Karl Sims}}
- {{cite web|url=http://www.xs4all.nl/~notnot/E-volverLUMC/E-volverLUMC.html|title=E-volver}}
- {{cite web|url=http://www.intlab.soka.ac.jp/~unemi/sbart|title=SBART, a program to evolve 2D images}}
- {{cite web|url=https://genjam.org|title=GenJam (Genetic Jammer)}}
- {{cite web|url=http://www.timblackwell.com/|title=Evolutionary music}}
- {{cite web|url=http://www.codeasart.com/poetry/darwin.html|title=Darwin poetry|url-status=dead|archiveurl=https://web.archive.org/web/20060412133402/http://www.codeasart.com/poetry/darwin.html|archivedate=2006-04-12}}
- {{cite web|url=http://www.design.kyushu-u.ac.jp/~takagi/TAKAGI/takagiLab.html|title=Takagi Lab at Kyushu University}}
- {{cite web|url=http://www.derrickcheng.com/Project/HBGA|title=Interactive one-max problem allows to compare the performance of interactive and human-based genetic algorithms|access-date=2006-12-03|archive-url=https://web.archive.org/web/20110709014211/http://derrickcheng.com/Project/HBGA/|archive-date=2011-07-09|url-status=dead}}.
- {{cite web|url=http://panmental.de/idiofact|title=Webpage that uses interactive evolutionary computation with a generative design algorithm to generate 2d images}}
- {{cite web|url=http://picbreeder.org/|title=Picbreeder service, Collaborative interactive evolution allowing branching from other users' creations that produces pictures like faces and spaceships|access-date=2007-08-02|archive-date=2011-07-25|archive-url=https://web.archive.org/web/20110725072615/http://picbreeder.org/|url-status=dead}}
- {{cite web|url=http://www.cse.unr.edu/~quiroz/|title=Peer to Peer IGA Using collaborative IGA sessions for floorplanning and document design}}
{{Evolutionary computation}}