Causal Learning: Psychology, Philosophy, and ComputationAlison Gopnik, Laura Schulz Oxford University Press, 22 мар. 2007 г. - Всего страниц: 384 Understanding causal structure is a central task of human cognition. Causal learning underpins the development of our concepts and categories, our intuitive theories, and our capacities for planning, imagination and inference. During the last few years, there has been an interdisciplinary revolution in our understanding of learning and reasoning: Researchers in philosophy, psychology, and computation have discovered new mechanisms for learning the causal structure of the world. This new work provides a rigorous, formal basis for theory theories of concepts and cognitive development, and moreover, the causal learning mechanisms it has uncovered go dramatically beyond the traditional mechanisms of both nativist theories, such as modularity theories, and empiricist ones, such as association or connectionism. |
Содержание
| 1 | |
CAUSATION AND INTERVENTION | 17 |
CAUSATION AND PROBABILITY | 115 |
CAUSATION THEORIES AND MECHANISMS | 241 |
Notes | 347 |
| 353 | |
Другие издания - Просмотреть все
Causal Learning: Psychology, Philosophy, and Computation Alison Gopnik,Laura Schulz Ограниченный просмотр - 2007 |
Causal Learning: Psychology, Philosophy, and Computation Alison Gopnik,Laura Schulz Ограниченный просмотр - 2007 |
Causal Learning: Psychology, Philosophy, and Computation Alison Gopnik,Laura Schulz,Laura Elizabeth Schulz Ограниченный просмотр - 2007 |
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