Author(s): Kenneth D. Forbus
Year: 2019
Contents
Preface
I. Introduction and Preliminaries
1. Introduction
1.1 Some Examples of Everyday Qualitative Reasoning
1.1.1 Heating Water
1.1.2 Does Cold Water Freeze Faster Than Warm Water?
1.1.3 The Seasons
1.1.4 Will These Collide?
1.1.5 Raven’s Progressive Matrices
1.1.6 Moral Decision Making
1.2 The Importance of Qualitative Reasoning in Human Cognition
1.3 Overview of the Book
2. Representation: An Overview
2.1 The Importance of Structured, Relational Representations
2.2 Logic, Formalism, and Precision
2.2.1 Syntax
2.3 Schemas, Frames, and Cases
2.4 Ontologies and Knowledge Bases
2.5 Richness and Structure of Predicate Vocabularies
2.6 Summary: Evaluating Representations
3. Reasoning: An Overview
3.1 Computational Complexity and Tractability
3.2 Deduction, Abduction, and Induction
3.3 Pattern Matching and Unification
3.3.1 Storing and Retrieving Knowledge
3.4 Closed-World Assumptions
3.5 Probability
4. Analogy
4.1 Some Psychologically Motivated Representation Conventions
4.2 Structure-Mapping Theory
4.3 Psychological Support for Structure-Mapping Theory
4.4 Computational Models of Analogical Processing
4.4.1 Matching
4.4.2 Retrieval
4.4.3 Generalization
4.5 The Centrality of Analogy in Human Cognition
II. Dynamics
5. Quantity
5.1 The Reals
5.2 Finite Approximations to the Reals
5.3 Finite Algebras and Fuzzy Logic
5.4 Signs
5.5 Ordinal Relations
5.6 Numerical Intervals
5.7 Order of Magnitude
5.8 Infinitesimals
5.9 Status Values
5.10 Summary
6. Relationships between Quantities
6.1 Why Qualitative Mathematics?
6.1.1 Soundness
6.1.2 Minimal Knowledge
6.1.3 Causality
6.2 Qualitative Mathematics in QP Theory
6.2.1 Direct Influences
6.2.2 Indirect Influences
6.2.3 Compositionality and Graceful Extension of Knowledge
6.2.4 Specifying Additional Information about Relationships
6.3 Naturalness
6.4 Expressiveness
6.5 Confluences and Causal Ordering
6.6 Summary
7. Qualitative Process Theory
7.1 Modeling the Modeling Process
7.2 Model Fragments
7.3 The Ontology of QP Theory
7.4 Basic Inferences of QP Theory
7.4.1 Model Formulation
7.4.2 Determining Activity
7.4.3 Resolving Influences
7.4.4 Limit Analysis
7.5 Encapsulated Histories
7.6 Summary
8. Examples Using QP Theory
8.1 Modeling Fluids
8.2 Existence and Why It Matters
8.3 Representing Contained Liquids
8.4 Representing Gases
8.5 Phase Changes
8.6 Boiling Water and Its Consequences
8.7 Ice Cubes in Freezers, Revisited
8.8 Modeling Motion
8.9 Modeling Materials
8.10 Modeling an Oscillator
8.11 Analyzing Stability
8.12 Discussion
9. Causality
9.1 What Is Causality?
9.2 Causality in QP Theory
9.3 Causality via Propagation
9.3.1 Causality in Confluence Models
9.3.2 Causal Ordering
9.4 Other Notions of Causality in Cognitive Science
9.5 Summary
10. Qualitative Simulation and Reasoning about Change
10.1 Qualitative Simulation
10.2 Existence and Continuity
10.3 Correctness of Qualitative Reasoning
10.3.1 Phase Space
11. Modeling
11.1 Example: A Steam Propulsion Plant
11.2 Compositional Modeling
11.2.1 Modeling Criteria
11.2.2 Representing Modeling Assumptions and Constraints
11.2.3 Structural Abstractions
11.3 Model Formulation Algorithms
11.4 How Might People Do Model Formulation?
12. Analogy in Dynamics
12.1 Mental Models and Runnability
12.2 Human Qualitative Reasoning: First Principles or Analogical?
12.2.1 Remembered Experience Model
12.2.2 Partial Generalization Model
12.2.3 Causally Annotated Experience Model
12.2.4 Generic Domain Theory
12.3 Similarity-Based Qualitative Simulation
12.3.1 A Prototype Similarity-Based Qualitative Simulator
12.4 Psychological Implications
12.4.1 Distribution of Reliance on Memory with Expertise
12.4.2 Differences in Novice/Expert Retrieval Patterns
12.4.3 Factors That Should Promote Expertise
12.5 Discussion
12.6 Summary
13. Dynamics in Language
13.1 Motivation
13.2 Recasting Qualitative Representations as Linguistic Frames
13.3 How QP Theory Manifests in English
13.3.1 Quantities
13.3.2 Ordinal Relationships
13.3.3 Influences
13.3.4 Model Fragments and Processes
13.4 Evidence
13.4.1 Corpus Analysis
13.4.2 Compatibility with Other Aspects of Semantics
13.4.3 Natural-Language Understanding Examples
13.5 Other Accounts
III. Space
14. Qualitative Spatial Reasoning: A Theoretical Framework
14.1 Reasoning about Motion through Space
14.2 The Metric Diagram/Place Vocabulary Model
14.2.1 The Poverty Conjecture
14.3 Other Examples of the MD/PV Model
14.4 Categorical/Coordinate Models in Psychology
14.5 A Unified Account
15. Qualitative Spatial Calculi
15.1 Example: Region Connection Calculus
15.2 A Collection of Calculi
15.2.1 Intersection Models of Topology
15.2.2 Distance Calculi
15.2.3 Orientation Calculi
15.3 Reasoning Issues
15.4 Summary
16. Understanding Sketches and Diagrams
16.1 Investigations of Sketching and Diagrams
16.2 The nuSketch Model of Sketch Understanding
16.3 CogSketch: Representations and Processing
16.4 Learning Spatial Prepositions
16.5 Reasoning about Depiction
16.6 Modeling Visual Problem Solving
16.6.1 Geometric Analogies
16.6.2 Raven’s Matrices
16.6.3 Oddity Task
16.6.4 What Makes an Effective Visual Problem Solver?
16.7 Summary
IV. Learning and Reasoning
17. Learning and Conceptual Change
17.1 A Framework for Mental Models in Physical Domains
17.2 Learning Protohistories
17.3 Constructing First-Principles Knowledge via Protohistory Statistics
17.4 Distributed Knowledge, Explanation Structure, and Conceptual Change
17.5 Learning via Cross-Domain Analogies
17.6 Summary
18. Commonsense Reasoning
18.1 How Common Sense Doesn’t Work
18.2 Some Psychological Considerations Concerning Common Sense
18.3 Quantitative Aspects of Common Sense
18.3.1 Analogical Estimation of Numerical Values
18.3.2 Qualitative Representations Can Enhance Similarity
18.3.3 Strategies for Back-of-the-Envelope Reasoning
18.3.4 How Well Does This Model Do?
18.4 Qualitative Representations in Conceptual Metaphors
18.5 Social Reasoning
18.5.1 Modeling Aspects of Emotions
18.5.2 Blame Assignment
18.5.3 Moral Decision Making
18.6 Summary
19. Expert Reasoning
19.1 Engineering Reasoning
19.1.1 Analysis
19.1.2 Monitoring, Control, and Diagnosis
19.1.3 Design
19.1.4 System Identification
19.2 Scientific Modeling
19.3 Summary
V. Summary and New Directions
20. Summary
20.1 Bridge between Perception and Cognition
20.2 Basis for Commonsense Reasoning
20.3 Foundation for Expert Reasoning
21. New Directions
21.1 Formalizing Discrete Processes and Their Interactions with Continuous Processes
21.2 Qualitative Vision
21.3 Qualitative Representations in Other Modalities
21.4 Qualitative Representations in Semantics
21.5 Qualitative Representations in Robotics
21.6 Cataloging the Range of Human Mental Models and Ontologies
21.7 Qualitative Representations for Social Science
21.8 Qualitative Representations in Cognitive Architecture
21.9 Multimodal Science Learning and Teaching
21.10 In Conclusion
Notes
References
Index
