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The discrepancy method is the glue that binds randomness and complexity. It is the bridge between randomized computation and discrepancy theory, the area of mathematics concerned with irregularities in distributions. The discrepancy method has played a major role in complexity theory; in particular, it has caused a mini-revolution of sorts in computational geometry. This book tells the story of the discrepancy method in a few short independent vignettes. It is a varied tale which includes such topics as communication complexity, pseudo-randomness, rapidly mixing Markov chains, points on the sphere and modular forms, derandomization, convex hulls, Voronoi diagrams, linear programming and extensions, geometric sampling, VC-dimension theory, minimum spanning trees, linear circuit complexity, and multidimensional searching. The mathematical treatment is thorough and self-contained. In particular, background material in discrepancy theory is supplied as needed. Thus the book should appeal to students and researchers in computer science, operations research, pure and applied mathematics, and engineering.
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Le langage algorithmique est d’une richesse expressive suffisante pour faire face à la haute complexité descriptive du monde vivant. Les circuits cellulaires, les bancs de poissons, les nuées d’oiseaux, la transmission de rumeurs, les mouvements de foule, la polarisation politique sont autant d’exemples de dynamique sociale qui se prêtent à la modélisation par les algorithmes naturels. L’algorithmique est essentielle à la science du XXIe siècle et constitue un des grands enjeux de l’informatique d’aujourd’hui.
Algorithms. --- Algorithms --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Theory --- Algorism --- Algebra --- Arithmetic --- Foundations --- algorithmique --- systèmes dynamiques --- sciences numériques --- informatique
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