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Reasoning with Probabilistic and Deterministic Graphical Models - Exact Algorithms, Second Edition (Paperback)
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Reasoning with Probabilistic and Deterministic Graphical Models - Exact Algorithms, Second Edition (Paperback)
Series: Synthesis Lectures on Artificial Intelligence and Machine Learning
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Graphical models (e.g., Bayesian and constraint networks, influence
diagrams, and Markov decision processes) have become a central
paradigm for knowledge representation and reasoning in both
artificial intelligence and computer science in general. These
models are used to perform many reasoning tasks, such as
scheduling, planning and learning, diagnosis and prediction,
design, hardware and software verification, and bioinformatics.
These problems can be stated as the formal tasks of constraint
satisfaction and satisfiability, combinatorial optimization, and
probabilistic inference. It is well known that the tasks are
computationally hard, but research during the past three decades
has yielded a variety of principles and techniques that
significantly advanced the state of the art. This book provides
comprehensive coverage of the primary exact algorithms for
reasoning with such models. The main feature exploited by the
algorithms is the model's graph. We present inference-based,
message-passing schemes (e.g., variable-elimination) and
search-based, conditioning schemes (e.g., cycle-cutset conditioning
and AND/OR search). Each class possesses distinguished
characteristics and in particular has different time vs. space
behavior. We emphasize the dependence of both schemes on few graph
parameters such as the treewidth, cycle-cutset, and (the
pseudo-tree) height. The new edition includes the notion of
influence diagrams, which focus on sequential decision making under
uncertainty. We believe the principles outlined in the book would
serve well in moving forward to approximation and anytime-based
schemes. The target audience of this book is researchers and
students in the artificial intelligence and machine learning area,
and beyond.
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