Knowledge Engineering: Building Cognitive Assistants for Evidence-based Reasoning.

-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
-References
-Appendixes

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.