Learning in Natural and Connectionist Systems [E-Book] : Experiments and a Model / by R. Hans Phaf.
Modern research in neural networks has led to powerful artificial learning systems, while recent work in the psychology of human memory has revealed much about how natural systems really learn, including the role of unconscious, implicit, memory processes. Regrettably, the two approaches typically i...
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Full text |
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Personal Name(s): | Phaf, R. Hans, author |
Imprint: |
Dordrecht :
Springer,
1994
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Physical Description: |
XVI, 294 p. online resource. |
Note: |
englisch |
ISBN: |
9789401108409 |
DOI: |
10.1007/978-94-011-0840-9 |
Subject (LOC): |
- Preface
- Acknowledgements
- 1: Introduction
- 1.1. The importance of learning
- 1.2. The biological role of learning
- 1.3. Connectionist models as learning systems
- 1.4. Models and languages
- 1.5. Aligning connectionist learning with natural learning
- 2: A connectionist approach to learning
- 2.1. The connectionist language
- 2.2. Problems with connectionist models
- 2.3. CALM: Categorizing and Learning Module
- 2.4. Single module simulations
- 2.5. Multiple module simulations
- 2.6. Discussion
- 3: Psychological constraints on learning
- 3.1. Attention and memory storage
- 3.2. Elaborative shifts during rehearsal
- 3.3. Attention and study-test compatibility as dissociative factors
- 3.4. Divided attention and implicit and explicit memory tasks
- 3.5. Towards a memory model incorporating attentional effects
- 4: A connectionist model for implicit and explicit memory
- 4.1. ELAN: a family of models
- 4.2. Architecture of ELAN-1
- 4.3. Simulations with ELAN-1
- 4.4. Higher ELAN models
- 5. Evaluation
- 5.1. Comparison to other models
- 5.2. The connectionism vs. symbol-manipulation controversy
- 5.3. Conclusion
- References.