Adaptivity and Learning
An Interdisciplinary Debate
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Beschreibung
Adaptivity and learning have in recent decades become a common concern of scientific disciplines. These issues have arisen in mathematics, physics, biology, informatics, economics, and other fields more or less simultaneously. The aim of this publication is the interdisciplinary discourse on the phenomenon of learning and adaptivity. Different perspectives are presented and compared to find fruitful concepts for the disciplines involved. The authors select problems showing representative traits concerning the frame up, the methods and the achievements rather than to present extended overviews.
To foster interdisciplinary dialogue, this book presents diverse perspectives from various scientific fields, including:
- The biological perspective: e.g., physiology, behaviour;
- The mathematical perspective: e.g., algorithmic and stochastic learning;
- The physics perspective: e.g., learning for artificial neural networks;
- The "learning by experience" perspective: reinforcement learning, social learning, artificial life;
- The cognitive perspective: e.g., deductive/inductive procedures, learning and language learning as a high level cognitive process;
- The application perspective: e.g., robotics, control, knowledge engineering.
Adaptivity and learning have in recent decades become a common concern of scientific disciplines. These issues have arisen in mathematics, physics, biology, informatics, economics, and other fields more or less simultaneously. The aim of this publication is the interdisciplinary discourse on the phenomenon of learning and adaptivity. Different perspectives are presented and compared to find fruitful concepts for the disciplines involved. The authors select problems showing representative traits concerning the frame up, the methods and the achievements rather than to present extended overviews.
There is no direct competition to this book which excels in the interdisciplinary case by case study of the various concepts of learning
Adaptivity and learning have in recent decades become a common concern of scientific disciplines. These issues have arisen in mathematics, physics, biology, informatics, economics, and other fields more or less simultaneously. The aim of this publication is the interdisciplinary discourse on the phenomenon of learning and adaptivity. Different perspectives are presented and compared to find fruitful concepts for the disciplines involved. The authors select problems showing representative traits concerning the frame up, the methods and the achievements rather than to present extended overviews.
Autor*in
Reimer Kühn
Themen in »Adaptivity and Learning«
Adaptation Mathematica artificial intelligence cognition complexity information processing issue learning machine learning mathematics networks neural network neural networks robot statistics