Book contents
- Frontmatter
- Contents
- List of boxes
- List of figures
- List of tables
- Preface
- Acknowledgments
- PART I Historical landmarks
- PART II The integration challenge
- PART III Information-processing models of the mind
- PART IV The organization of the mind
- PART V New horizons
- 13 New horizons: Dynamical systems and situated cognition
- 14 Looking ahead: Challenges and applications
- Glossary
- Bibliography
- Index
14 - Looking ahead: Challenges and applications
from PART V - New horizons
- Frontmatter
- Contents
- List of boxes
- List of figures
- List of tables
- Preface
- Acknowledgments
- PART I Historical landmarks
- PART II The integration challenge
- PART III Information-processing models of the mind
- PART IV The organization of the mind
- PART V New horizons
- 13 New horizons: Dynamical systems and situated cognition
- 14 Looking ahead: Challenges and applications
- Glossary
- Bibliography
- Index
Summary
Cognitive science has already given us many important insights into the human mind. We have explored a good number of these in this book. As I have tried to bring out, these insights all stem from the single basic idea governing cognitive science as the interdisciplinary science of the mind. This is the idea that mental operations are information-processing operations.
This book began by looking at how this way of thinking about the mind first emerged out of developments in seemingly disparate subjects, such as mathematical logic, linguistics, psychology, and information theory. Most of the significant early developments in cognitive science explored the parallel between information processing in the mind and information processing in a digital computer. As cognitive scientists and cognitive neuroscientists developed more sophisticated tools for studying and modeling the brain, the information-processing principle was extended in new directions and applied in new ways.
Later chapters explored in detail the two computing approaches to information processing that have dominated the development of cognitive science. According to the physical symbol system hypothesis, we need to think about information processing in terms of the rule-governed transformation of physical structures. These physical structures are information-carrying representations.
Neural network modelers think of information processing somewhat differently. Information in neural networks does not have to be carried by discrete and independent structures. It can be distributed across patterns of weights and connectivity in a neural network. And information processing seems to work differently.
- Type
- Chapter
- Information
- Cognitive ScienceAn Introduction to the Science of the Mind, pp. 456 - 462Publisher: Cambridge University PressPrint publication year: 2010