For nearly two decades, Kenneth Forbus and Johan de Kleer have accumulated a substantial body of knowledge about the principles and practice of creating problem solvers. In some cases they are the inventors of the ideas or techniques described, and in others, participants in their development.Building Problem Solvers communicates this knowledge in a focused, cohesive manner. It is unique among standard artificial intelligence texts in combining science and engineering, theory and craft to describe the construction of AI reasoning systems, and it includes code illustrating the ideas.After working through Building Problem Solvers, readers should have a deep understanding of pattern directed inference systems, constraint languages, and truth maintenance systems. The diligent reader will have worked through several substantial examples, including systems that perform symbolic algebra, natural deduction, resolution, qualitative reasoning, planning, diagnosis, scene analysis, and temporal reasoning.Kenneth D. Forbus is Professor of Computer Science and Education at the Institute for Learning Sciences, Northwestern University. Johan de Kleer directs the Systems and Practices Laboratory at the Xerox Palo Alto Research Center. For nearly two decades, Kenneth Forbus and Johan de Kleer have accumulated a substantial body of knowledge about the principles and practice of creating problem solvers. In some cases they are the inventors of the ideas or techniques described, and in others, participants in their development. This book communicates this knowledge in a focused, cohesive manner. It is unique among standard artificial intelligence texts in combining science and engineering, theory and craft to describe the construction of AI reasoning systems, and it includes code illustrating the ideas. After working through the text, readers should have a deep understanding of pattern directed inference systems, constraint languages, and truth-maintenance systems. The diligent reader will have worked through several substantial examples, including systems that perform symbolic algebra, natural deduction, resolution, qualitative reasoning, planning, diagnosis, scene analysis, and temporal reasoning. Along the way Forbus and de Kleer teach the art of building robust AI software. They begin with simple examples such as search programs, and move to more complex cases on the cutting edge of AI techniques, such as model-based diagnosis systems and a qualitative reasoner. Although this book is designed primarily as a text for advanced AI classes or AI programming classes, it can be used by researchers in universities and industrial laboratories who want to apply these techniques in their work, and by programmers who want to incorporate these ideas in their applications. Series Foreword Preface Introduction Classical Problem Solving Pattern-Directed Inference Systems Extending Pattern-Directed Inference Systems Introduction to Truth Maintenance Systems Justification-Based Truth Maintenance Systems Putting the JTMS to Work Logic-Based Truth Maintenance Systems Putting an LTMS to Work Implementing Qualitative Process Theory Assumption-Based Truth Maintenance Systems Improving the Completeness of Truth Maintenance Systems Putting the ATMS to Work Antecedent Constraint Languages Assumption-Based Constraint Languages A Tiny Diagnosis Engine Symbolic Relaxation Systems Some Frontiers Putting the Programs to Work Index Kenneth D. Forbus, Johan De Kleer. A Bradford Book. Includes Bibliographical References And Index.
