D. Floreano. Ago ergo sum. Mulhauser, G., editor, Evolving Consciousness, 1997. Home/Search Document Details and Download
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Robot Control and the Evolution of Modular Neurodynamics - Pasemann, Steinmetz.. (2001) (Correct)
....of a synthetical approach to neural systems based on ideas coming from elds like embodied cognition [29] arti cial life [18] 1] dynamical systems and modular recurrent neural networks. Evolutionary computation techniques will be used as has been suggested for instance in [5] 15] 10] [13], 24] The combined application of neural networks and evolutionary algorithms turned out to be a very e ective tool for general problem solving [33] It was also shown to generate interesting classes of robot behaviors (see e.g. 23] Instead of standard genetic algorithms, here an ENS 3 ....
Floreano, D. (1997) Ago ergo sum, in: Mulhauser, G (Ed.), Evolving Consciousness, J. Benjamins, Amsterdam.
Co-Evolution and Ontogenetic Change in Competing Robots - Floreano, Nolfi, Mondada (1999) (3 citations) Self-citation (Floreano) (Correct)
....of challenges [31] that might favor fast emergence of complex solutions. 3. 3 Selection criteria In artificial evolution the choice of the selection criterion (fitness function) can make the difference between trivial parameter optimization and generation of creative and life like solutions [7]. From an engineering point of view, it might seem reasonable to pursue an optimization approach by designing a detailed fitness function that attempts to develop behaviors that are partially pre defined. However, by doing so one might also include wrong assumptions that derive from an ....
D. Floreano. Ago Ergo Sum. In G. Mulhauser, editor, Evolving Consciousness. Benjamins Press, New York, 1997.
Competitive Co-Evolutionary Robotics: From Theory to Practice - Floreano, Nolfi, Mondada (1998) (11 citations) Self-citation (Floreano) (Correct)
....in section 1. and indicate its efficacy from an optimization perspective. 4. 2 Selection criteria In artificial evolution the choice of the selection criterion (fitness function) can make the difference between trivial parameter optimization and generation of creative and life like solutions (Floreano, 1997). From an engineering point of view, one might think that it makes sense to pursue an optimization approach by including several constraints in the function in the attempt to describe the expected behavior. However, by doing so one might also include wrong assumptions that derive from an ....
Floreano, D. (1997). Ago Ergo Sum. In Mulhauser, G., editor, Evolving Consciousness. Benjamins Press, New York.
Pro-active agents - With Recurrent Neural (Correct)
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D. Floreano. Ago ergo sum. Mulhauser, G., editor, Evolving Consciousness, 1997.
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