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Growing Adaptive Machines Combining Development and Learning in Artificial Neural Networks /
The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that a...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2014.
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| Edición: | 1st ed. 2014. |
| Colección: | Studies in Computational Intelligence,
557 |
| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- Artificial neurogenesis: An introduction and selective review
- A Brief Introduction to Probabilistic Machine Learning and its Relation to Neuroscience
- Evolving culture versus local minima
- Learning sparse features with an auto-associator
- HyperNEAT: the first five years
- Using the GReaNs (Genetic Regulatory evolving artificial Networks) platform for signal processing, animat control, and artificial multicellular development
- Constructing complex systems via activity-driven unsupervised Hebbian self-organization
- Neuro-centric and holocentric approaches to the evolution of developmental neural networks
- Artificial evolution of plastic neural networks: A few key concepts.