1. Declarative Knowledge
1.1. Concepts
1.1.1. Classical
1.1.2. Fuzzy
1.1.3. Essentialism
1.1.4. Intelligence and Concepts in Different Cultures
1.2. Categories
1.2.1. Feature-based theory
1.2.2. Prototype theory
1.2.3. Exemplar Theory
1.2.4. Synthesis: Feature-based + prototypes
1.2.5. Theory view of categorization
1.3. Semantic Network Models
1.3.1. Collins & Quillian’s Network Model
1.3.1.1. Node
1.3.1.2. Labeled Relationships
1.3.1.3. Concept of Inheritance
1.3.2. Comparing Semantic Features
1.4. Schematic Representations
1.4.1. Schemas
1.4.1.1. Characteristics of Schema
1.4.1.2. Information about Relationships
1.4.2. Scripts
1.4.2.1. Typicality Effect
2. Integrative Models for Representing Declarative and Nondeclarative Knowledge
2.1. Combining Representations: ACT-R
2.1.1. ACT - Adaptive Control of Thought
2.1.1.1. Proposition
2.1.2. ACT-R (Adaptive Control of Thought - Rational)
2.1.2.1. Temporal Information/Temporal Strings
2.1.2.2. Declarative Knowledge within ACT-R
2.1.2.2.1. Spreading Activation
2.1.2.3. Procedural Knowledge within ACT-R
2.1.2.3.1. Proceduralization
2.2. Parallel Processing: The Connectionist Model
2.2.1. Parallel Distributed Processing (PDP) Model
2.2.2. How does Parallel Distributed Processing Model work?
2.2.2.1. Inactive Neurons
2.2.2.2. Excitatory Neurons
2.2.2.3. Inhibitory Neurons
2.3. Neural Network Model
3. Nondeclarative Knowledge
3.1. Procedural Knowledge
3.1.1. Serial Processing
3.1.1.1. Production System
3.1.1.1.1. Production
3.1.1.1.2. Bugs
3.2. Associative Knowledge (conditioning)
3.3. Nonassociative Knowledge
3.4. Priming
3.4.1. Semantic Priming
3.4.2. Repetition Priming