Unifying the mind : cognitive representations as graphical models /
Saved in:
| Author / Creator: | Danks, David, 1975- author. |
|---|---|
| Imprint: | Cambridge, Massachusetts : The MIT Press, [2014] |
| Description: | xi, 287 pages : illustrations ; 24 cm |
| Language: | English |
| Subject: | |
| Format: | Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/10086357 |
Table of Contents:
- Acknowledgments
- 1. öFree-Rangeö Cognition
- 1.1. Thinking across Boundaries
- 1.2. Cognitive Representations, Graphical Models, and Cognitive Unification
- 1.3. Where Are We Going?
- 2. Computational Realism, Levels, and Constraints
- 2.1. What Is a Computational Cognitive Model?
- 2.2. A Proliferation of Levels
- 2.3. Previous Accounts of Intertheoretic Relations
- 2.4. Connecting Theories through Constraints
- 2.5. Putting the Pieces Together
- 3. A Primer on Graphical Models
- 3.1. Graphical Models as Representations of Relevance
- 3.2. Directed Acyclic Graph (DAG) Models
- 3.3. Undirected Graph (UG) Models
- 3.4. Expressive Power of Graphical Models
- 4. Causal Cognition
- 4.1. A Taxonomy of Causal Cognition
- 4.2. Causal Inference
- 4.3. Causal Reasoning
- 4.4. Causal Perception
- 4.5. Conclusion
- 5. Concepts, Categories, and Inference
- 5.1. Concepts as Fundamental Building Blocks
- 5.2. Concepts, Probability Distributions, and Graphical Models
- 5.3. Reasoning with Concepts
- 5.4. Building Webs
- 5.5. Putting Together the (Mathematical) Pieces
- 5.6. Conclusion
- 6. Decision Making via Graphical Models
- 6.1. Roles for Causal Knowledge in Decision Making
- 6.2. Novel Decision-Making Algorithms
- 6.3. Graphical-Model-Based Decision Making
- 7. Unifying Cognition
- 7.1. Shared Representations and Unified Cognition
- 7.2. What Do the Data Say?
- 7.3. Novel Predictions, New Experiments, and Open Questions
- 8. Alternative Approaches
- 8.1. Different Approaches for Unifying the Mind
- 8.2. Schema-Centered Unifications
- 8.3. Process-Centered Unifications
- 9. Broader Implications
- 9.1. Rethinking the Notion of Modularity
- 9.2. The Challenge of Multiple Relevance Types
- 9.3. Neurons, Processes, Rationality, and Representations
- 10. Conclusions, Open Questions, and Next Steps
- 10.1. Where Do We Go from Here?
- Appendix: Graphical Models and Concepts*
- Notes
- References
- Index
