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Interactive genetic algorithm (IGA) is defined as a genetic algorithm that use 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. Interactive computation methods can use different representations, both linear (as in traditional genetic algorithms) and tree-like ones (as in genetic programming).1 See also
Interactive evolutionary computation, Evolutionary art, Karl Sims, Human-based genetic algorithm, Human-computer interaction
2 References
- Cheng, Chihyung Derrick and Kosorukoff, Alex (2004), Interactive one-max problem allows to compare the performance of interactive and human-based genetic algorithms. Genetic and Evolutionary Computational Conference, GECCO-2004.
- Takagi, H. (2000). Active user intervention in an EC Search. Proceesings of the JCIS 2000.
- Takagi, H. (2001). Interactive Evolutionary Computation: Fushion of the Capacities of EC Optimization and Human Evaluation. Proceesings of the IEEE 89, 9, pp. 1275-1296
3 External links
- [1] - Interactive one-max problem allows to compare the performance of interactive and human-based genetic algorithms.
Evolutionary algorithms
Interactive evolutionary computation
Human-computer interaction
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