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One of the great achievements of contemporary mathematics is the new understanding of four dimensions. Michael Freedman and Frank Quinn have been the principals in the geometric and topological development of this subject, proving the Poincar and Annulus conjectures respectively. Recognition for this work includes the award of the Fields Medal of the International Congress of Mathematicians to Freedman in 1986. In Topology of 4-Manifolds these authors have collaborated to give a complete and accessible account of the current state of knowledge in this field. The basic material has been considerably simplified from the original publications, and should be accessible to most graduate students. The advanced material goes well beyond the literature; nearly one-third of the book is new. This work is indispensable for any topologist whose work includes four dimensions. It is a valuable reference for geometers and physicists who need an awareness of the topological side of the field.Originally published in 1990.The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

Differential topology --- Four-manifolds (Topology) --- Trois-variétés (Topologie) --- Vier-menigvuldigheden (Topologie) --- 4-dimensional manifolds (Topology) --- 4-manifolds (Topology) --- Four dimensional manifolds (Topology) --- Manifolds, Four dimensional --- Low-dimensional topology --- Topological manifolds --- 4-manifold. --- Ambient isotopy. --- Annulus theorem. --- Automorphism. --- Baire category theorem. --- Bilinear form. --- Boundary (topology). --- CW complex. --- Category of manifolds. --- Central series. --- Characterization (mathematics). --- Cohomology. --- Commutative diagram. --- Commutative property. --- Commutator subgroup. --- Compactification (mathematics). --- Conformal geometry. --- Connected sum. --- Connectivity (graph theory). --- Cyclic group. --- Diagram (category theory). --- Diameter. --- Diffeomorphism. --- Differentiable manifold. --- Differential geometry. --- Dimension. --- Disk (mathematics). --- Duality (mathematics). --- Eigenvalues and eigenvectors. --- Embedding problem. --- Embedding. --- Equivariant map. --- Fiber bundle. --- Four-dimensional space. --- Fundamental group. --- General position. --- Geometry. --- H-cobordism. --- Handlebody. --- Hauptvermutung. --- Homeomorphism. --- Homology (mathematics). --- Homology sphere. --- Homomorphism. --- Homotopy group. --- Homotopy sphere. --- Homotopy. --- Hurewicz theorem. --- Hyperbolic geometry. --- Hyperbolic group. --- Hyperbolic manifold. --- Identity matrix. --- Intermediate value theorem. --- Intersection (set theory). --- Intersection curve. --- Intersection form (4-manifold). --- Intersection number (graph theory). --- Intersection number. --- J-homomorphism. --- Knot theory. --- Lefschetz duality. --- Line–line intersection. --- Manifold. --- Mapping cylinder. --- Mathematical induction. --- Metric space. --- Metrization theorem. --- Module (mathematics). --- Normal bundle. --- Parametrization. --- Parity (mathematics). --- Product topology. --- Pullback (differential geometry). --- Regular homotopy. --- Ring homomorphism. --- Rotation number. --- Seifert–van Kampen theorem. --- Sesquilinear form. --- Set (mathematics). --- Simply connected space. --- Smooth structure. --- Special case. --- Spin structure. --- Submanifold. --- Subset. --- Support (mathematics). --- Tangent bundle. --- Tangent space. --- Tensor product. --- Theorem. --- Topological category. --- Topological manifold. --- Transversal (geometry). --- Transversality (mathematics). --- Transversality theorem. --- Uniqueness theorem. --- Unit disk. --- Vector bundle. --- Whitehead torsion. --- Whitney disk.

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This self-contained introduction to the distributed control of robotic networks offers a distinctive blend of computer science and control theory. The book presents a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation. The unifying theme is a formal model for robotic networks that explicitly incorporates their communication, sensing, control, and processing capabilities--a model that in turn leads to a common formal language to describe and analyze coordination algorithms. Written for first- and second-year graduate students in control and robotics, the book will also be useful to researchers in control theory, robotics, distributed algorithms, and automata theory. The book provides explanations of the basic concepts and main results, as well as numerous examples and exercises. Self-contained exposition of graph-theoretic concepts, distributed algorithms, and complexity measures for processor networks with fixed interconnection topology and for robotic networks with position-dependent interconnection topology Detailed treatment of averaging and consensus algorithms interpreted as linear iterations on synchronous networks Introduction of geometric notions such as partitions, proximity graphs, and multicenter functions Detailed treatment of motion coordination algorithms for deployment, rendezvous, connectivity maintenance, and boundary estimation

Robotics. --- Computer algorithms. --- Robots --- Automation --- Machine theory --- Robot control --- Robotics --- Algorithms --- Control systems. --- Computer algorithms --- Control systems --- 1-center problem. --- Adjacency matrix. --- Aggregate function. --- Algebraic connectivity. --- Algebraic topology (object). --- Algorithm. --- Analysis of algorithms. --- Approximation algorithm. --- Asynchronous system. --- Bellman–Ford algorithm. --- Bifurcation theory. --- Bounded set (topological vector space). --- Calculation. --- Cartesian product. --- Centroid. --- Chebyshev center. --- Circulant matrix. --- Circumscribed circle. --- Cluster analysis. --- Combinatorial optimization. --- Combinatorics. --- Communication complexity. --- Computation. --- Computational complexity theory. --- Computational geometry. --- Computational model. --- Computer simulation. --- Computer vision. --- Connected component (graph theory). --- Connectivity (graph theory). --- Consensus (computer science). --- Control function (econometrics). --- Differentiable function. --- Dijkstra's algorithm. --- Dimensional analysis. --- Directed acyclic graph. --- Directed graph. --- Discrete time and continuous time. --- Disk (mathematics). --- Distributed algorithm. --- Doubly stochastic matrix. --- Dynamical system. --- Eigenvalues and eigenvectors. --- Estimation. --- Euclidean space. --- Function composition. --- Hybrid system. --- Information theory. --- Initial condition. --- Instance (computer science). --- Invariance principle (linguistics). --- Invertible matrix. --- Iteration. --- Iterative method. --- Kinematics. --- Laplacian matrix. --- Leader election. --- Linear dynamical system. --- Linear interpolation. --- Linear programming. --- Lipschitz continuity. --- Lyapunov function. --- Markov chain. --- Mathematical induction. --- Mathematical optimization. --- Mobile robot. --- Motion planning. --- Multi-agent system. --- Network model. --- Network topology. --- Norm (mathematics). --- Numerical integration. --- Optimal control. --- Optimization problem. --- Parameter (computer programming). --- Partition of a set. --- Percolation theory. --- Permutation matrix. --- Polytope. --- Proportionality (mathematics). --- Quantifier (logic). --- Quantization (signal processing). --- Robustness (computer science). --- Scientific notation. --- Sensor. --- Set (mathematics). --- Simply connected space. --- Simulation. --- Simultaneous equations. --- State space. --- State variable. --- Stochastic matrix. --- Stochastic. --- Strongly connected component. --- Synchronous network. --- Theorem. --- Time complexity. --- Topology. --- Variable (mathematics). --- Vector field.

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This accessible book provides an introduction to the analysis and design of dynamic multiagent networks. Such networks are of great interest in a wide range of areas in science and engineering, including: mobile sensor networks, distributed robotics such as formation flying and swarming, quantum networks, networked economics, biological synchronization, and social networks. Focusing on graph theoretic methods for the analysis and synthesis of dynamic multiagent networks, the book presents a powerful new formalism and set of tools for networked systems. The book's three sections look at foundations, multiagent networks, and networks as systems. The authors give an overview of important ideas from graph theory, followed by a detailed account of the agreement protocol and its various extensions, including the behavior of the protocol over undirected, directed, switching, and random networks. They cover topics such as formation control, coverage, distributed estimation, social networks, and games over networks. And they explore intriguing aspects of viewing networks as systems, by making these networks amenable to control-theoretic analysis and automatic synthesis, by monitoring their dynamic evolution, and by examining higher-order interaction models in terms of simplicial complexes and their applications. The book will interest graduate students working in systems and control, as well as in computer science and robotics. It will be a standard reference for researchers seeking a self-contained account of system-theoretic aspects of multiagent networks and their wide-ranging applications. This book has been adopted as a textbook at the following universities: ? University of Stuttgart, Germany Royal Institute of Technology, Sweden Johannes Kepler University, Austria Georgia Tech, USA University of Washington, USA Ohio University, USA

Network analysis (Planning) --- Multiagent systems --- Agent-based model (Computer software) --- MASs (Multiagent systems) --- Multi-agent systems --- Systems, Multiagent --- Intelligent agents (Computer software) --- Project networks --- Planning --- System analysis --- Graphic methods. --- Mathematical models. --- Mathematical models --- Graphic methods --- Addition. --- Adjacency matrix. --- Algebraic graph theory. --- Algorithm. --- Automorphism. --- Bipartite graph. --- Cardinality. --- Cartesian product. --- Circulant graph. --- Combinatorics. --- Complete graph. --- Computation. --- Connectivity (graph theory). --- Controllability. --- Convex combination. --- Corollary. --- Cycle graph (algebra). --- Cycle space. --- Degree (graph theory). --- Degree matrix. --- Diagonal matrix. --- Diameter. --- Differentiable function. --- Dimension. --- Directed graph. --- Division by zero. --- Dynamical system. --- Eigenvalues and eigenvectors. --- Equilibrium point. --- Estimation. --- Estimator. --- Existential quantification. --- Extremal graph theory. --- Graph (discrete mathematics). --- Graph theory. --- Identity matrix. --- Incidence matrix. --- Information exchange. --- Initial condition. --- Interconnection. --- Iteration. --- Kalman filter. --- Kronecker product. --- LTI system theory. --- LaSalle's invariance principle. --- Laplacian matrix. --- Least squares. --- Line graph. --- Linear map. --- Lipschitz continuity. --- Lyapunov function. --- Lyapunov stability. --- Markov chain. --- Mathematical optimization. --- Matrix exponential. --- Measurement. --- Multi-agent system. --- Nash equilibrium. --- Natural number. --- Network topology. --- Nonnegative matrix. --- Notation. --- Observability. --- Optimal control. --- Optimization problem. --- Pairwise. --- Parameter. --- Path graph. --- Permutation matrix. --- Permutation. --- Positive semidefinite. --- Positive-definite matrix. --- Probability. --- Quantity. --- Random graph. --- Random variable. --- Rate of convergence. --- Requirement. --- Result. --- Robotics. --- Scientific notation. --- Sensor. --- Sign (mathematics). --- Simplicial complex. --- Special case. --- Spectral graph theory. --- Stochastic matrix. --- Strongly connected component. --- Subset. --- Summation. --- Supergraph. --- Symmetric matrix. --- Systems theory. --- Theorem. --- Theory. --- Unit interval. --- Upper and lower bounds. --- Variable (mathematics). --- Vector space. --- Without loss of generality.