Coevolutionary Computation
By J. Paredis. 1995
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- J. Urgen Schmidhuber
- Sergey Levine
- Yoshua Bengio
- Faustino J. Gomez
- Kenneth O. Stanley
- Shimon Whiteson
- Risto Miikkulainen
- Pieter Abbeel
Citations in the corpus
- Emergent Tool Use From Multi-Agent Autocurricula (2019, background): “Early work explored self-play using genetic algorithms [16, 17, 18, 19].”
- Multiagent Learning: Basics, Challenges, and Prospects (2012, background): “Techniques explored in these first multiagent learning contexts were early ant systems and flocking or herding behavior (Manderick and Moyson 1988; Colorni, Dorigo, and Maniezzo 1992; Banerjee 1992), evolutionary computation (Manderick and Spiessens 1989; Steels 1987, 1988; Paredis 1995), social lea”
- Robust non-linear control through neuroevolution (2003, methodology): “This approach has been used in learning classifiers implemented by a neural network, in coevolution of cascade correlation networks, and in coevolution of radial basis functions (Eriksson and Olsson 1997; Horn et al. 1994; Paredis 1995; Whitehead and Choate 1995).”
- Evolution of Cartesian Genetic Programs for Development of Learning Neural Architecture (2011, background): “Paredis describes this type of fitness as “life-time fitness evaluation” and discusses how this “arms race” provides a strong driving force toward complexity (Paredis, 1995).”
- Forming Neural Networks Through Efficient and Adaptive Coevolution (1997, methodology): “Cooperative Coevolutionary algorithms (Horn, Goldberg, & Deb, 1994; Moriarty & Miikkulainen, 1996a; Paredis, 1995; Potter, De Jong, & Grefenstette, 1995; Smith, Forrest, & Perelson, 1993; Whitehead & Choate, 1995) o er a promising alternative to the canonical EA in di cult and dynamic problems.”
- Accelerated Neural Evolution through Cooperatively Coevolved Synapses (2008, methodology): “This approach has been used in learning neural network classifiers, in coevolution of cascade correlation networks, and in coevolution of radial basis functions (Eriksson and Olsson, 1997; Horn et al., 1994; Paredis, 1995; Whitehead and Choate, 1995).”