Building Problem Solvers Listings - 3.5

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. 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. This software has been tested and used extensively by graduate students and programmers in industry. Although Building Problem Solvers 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.