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Full Description
This book presents a significant advancement in the theory and practice of knowledge engineering, the discipline concerned with the development of intelligent agents that use knowledge and reasoning to perform problem solving and decision-making tasks. It covers the main stages in the development of a knowledge-based agent: understanding the application domain, modeling problem solving in that domain, developing the ontology, learning the reasoning rules, and testing the agent. The book focuses on a special class of agents: cognitive assistants for evidence-based reasoning that learn complex problem-solving expertise directly from human experts, support experts, and nonexperts in problem solving and decision making, and teach their problem-solving expertise to students. A powerful learning agent shell, Disciple-EBR, is included with the book, enabling students, practitioners, and researchers to develop cognitive assistants rapidly in a wide variety of domains that require evidence-based reasoning, including intelligence analysis, cybersecurity, law, forensics, medicine, and education.
Contents
1. Introduction; 2. Evidence-based reasoning: connecting the dots; 3. Methodologies and tools for agent design and development; 4. Modeling the problem-solving process; 5. Ontologies; 6. Ontology design and development; 7. Reasoning with ontologies and rules; 8. Learning for knowledge-based agents; 9. Rule learning; 10. Rule refinement; 11. Abstraction of reasoning; 12. Disciple agents; 13. Design principles for cognitive assistants.
