Prodigy
Architecture
Philosophy and Methodological Assumptions
Description of the Architecture
Learning Modules
Agent Properties
Style of Control
Forward and Backward Chaining
Modular Organization
Symbolic World Model (Global State)
Glass Box Approach
Declarative Representations
Global Representation and Uniform Access to Knowledge
Homogeneous (Uniform) Knowledge Representation
First-Order Logic Representation
STRIPS-like Representation
Deliberative Learning
Generalization
Monotonic Learning
The Utility Function
Means-End Analysis Technique
Deliberation/Operation Speed
Casual Commitment
List of Agent Properties for All Architectures
Capabilities
Multi-Method Learning
Explanation-Based Learning
Static Analysis for Control Rule Learning
Analogical Learning
Abstraction Learning
Refining and Correcting Domain Knowledge
Learning from an Expert
Planning
Problem Solving
Meta-Reasoning
Self-Reflection
Prediction
Focused Behavior and Processing
List of Capabilities for All Architectures
Environmental Considerations
Static Environments
Environmental Consistency
Simulated Environments
Knowledge-Rich
Complete Knowledge
Learning Cost
List of Environmental Considerations for All Architectures
Issues
References
Table of Contents
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