Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation

By Hideyuki Takagi. Proceedings of the IEEE, 2001

1,479 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/f254a47197d122d0d345392786215ad9cd7c3f56

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In Computer Vision and Pattern Recognition

In Signal Processing

Citations in the corpus

Picbreeder: A Case Study in Collaborative Evolutionary Exploration of Design Space (2011, positive): “Interactive evolutionary computation (IEC; Takagi, 2001 ), that is, artificial evolution guided through human direction, is such a tool that can potentially assist the design process.,In single-user interactive evolution ( Takagi, 2001 ), the user is presented with a set of alternatives generated b”
Evolutionary algorithms and their applications to engineering problems (2020, background): “Interactive GA [17] Takagi The fitness of individuals is assigned by human rather by a function 2001”
Surrogate-assisted evolutionary computation: Recent advances and future challenges (2011, background): “In interactive evolutionary computation, the fitness value of each individual is evaluated by human user subjectively [68].”
Breeding a diversity of Super Mario behaviors through interactive evolution (2016, neutral): “org/wiki/Super Mario Maker a variety of different domains [9, 19, 21], because they allow human intuition to guide the search process.”
Social media big data analytics: A survey (2019, neutral): “Takagi (2001).”
Search-Based Procedural Content Generation: A Taxonomy and Survey (2011, methodology): “The explicit interactive evaluation function (which is similar to functions commonly used in evolutionary art [ 68 ]), works as follows: each “generation” the user selects two parent buildings and the system produces a new screen of 16 offspring buildings.”
A Field Guide to Genetic Programming (2008, background): “Most approaches to evolving music have made at least some use of interactive evolution (Takagi, 2001) in which the fitness of programs is provided by users, often via the Internet (Ando, Dahlsted, Nordahl, and Iba, 2007; Chao and Forrest, 2003).”
The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities (2018, neutral): “At first glance it may seem that interactive evolution [133] is unlikely to surprise anyone, because of close and constant interactions with the user.”