Knowledge Engineering: Building Cognitive Assistants for Evidence-based Reasoning

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.

Table of Contents

Chapter 1 Introduction
Chapter 2 Evidence-based Reasoning: Connecting the Dots
Chapter 3 Methodologies and Tools for Agent Design and Development
Chapter 4 Modeling the Problem-Solving Process
Chapter 5 Ontologies
Chapter 6 Ontology Design and Development
Chapter 7 Reasoning with Ontologies and Rules
Chapter 8 Learning for Knowledge-based Agents
Chapter 9 Rule Learning
Chapter 10 Rule Refinement
Chapter 11 Abstraction of Reasoning
Chapter 12 Disciple Agents
Chapter 13 Design Principles for Cognitive Assistants