This is the second volume of a systematic two-volume presentation of the various areas of research in the field of structural complexity. The mathematical theory of computation has developed into a broad and rich discipline within which the theory of algorithmic complexity can be approached from several points of view. This volume is addressed to graduate students and researchers and assumes knowledge of the topics treated in the first volume but is otherwise nearly self-contained. Topics covered include vector machines, parallel computation, alternation, uniform circuit complexity, isomorphism, biimmunity and complexity cores, relativization and positive relativization, the low and high hierarchies, Kolmogorov complexity and probability classes. Numerous exercises and references are given.
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Most Helpful Customer Reviews
0 of 4 people found the following review helpful:
3.0 out of 5 stars
A decent graduate text on structural complexity,
By Todd Ebert (Long Beach California) - See all my reviews
This review is from: Structural Complexity II (Theoretical Physics) (Hardcover)
This book and it's volume I counterpart have a place in complexity theory, but not as a first introduction to the subject (for which I had to use it for). For a first introduction, read Papadimitiou's excellent book. This book is more appropriate for researchers in the field.
0 of 5 people found the following review helpful:
3.0 out of 5 stars
A decent book for beginning researchers,
By Todd Ebert (Long Beach California) - See all my reviews
This review is from: Structural Complexity I (Texts in Theoretical Computer Science. An EATCS Series) (Hardcover)
If you are learning about complexity theory for the first time, I recommend you read Papadimitriou's excellent book on the subject. One aspect about this book that I did not like is it's lack of combinatorial analysis, and its more generic, structural apporoach (i.e. focusing on robust sets of problems). Some may prefer this, but I think the combinatorial approach is more in line with mainstream computer science.
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