Open AccessBook
Optimization and nonsmooth analysis
TLDR
The Calculus of Variations as discussed by the authors is a generalization of the calculus of variations, which is used in many aspects of analysis, such as generalized gradient descent and optimal control.Abstract:
1. Introduction and Preview 2. Generalized Gradients 3. Differential Inclusions 4. The Calculus of Variations 5. Optimal Control 6. Mathematical Programming 7. Topics in Analysis.read more
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Journal ArticleDOI
Distributed algorithms for reaching consensus on general functions
TL;DR: This paper identifies a class of smooth functions for which one can synthesize in a systematic way distributed algorithms that achieve consensus, applies this result to the family of weighted power mean functions, and characterize the exponential convergence properties of the resulting algorithms.
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Simultaneous Variable Selection
TL;DR: A new method for selecting a common subset of explanatory variables where the aim is to model several response variables based on the (joint) residual sum of squares while constraining the parameter estimates to lie within a suitable polyhedral region is proposed.
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Proximity control in bundle methods for convex
TL;DR: A technique is given for choosing {uk} adaptively that eliminates sensitivity to objective scaling and some encouraging numerical experience is reported.
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Coordination and Geometric Optimization via Distributed Dynamical Systems
Jorge E. Cortes,Francesco Bullo +1 more
TL;DR: In this paper, a collection of distributed control laws that are related to nonsmooth gradient systems for disk-covering and sphere-packing problems is presented. And the resulting dynamical systems promise to be of use in coordination problems for networked robots; in this setting the distributed control law correspond to local interactions between the robots.
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A novel actor-critic-identifier architecture for approximate optimal control of uncertain nonlinear systems
Shubhendu Bhasin,Rushikesh Kamalapurkar,Marcus Johnson,Kyriakos G. Vamvoudakis,Frank L. Lewis,Warren E. Dixon +5 more
TL;DR: An online adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem for continuous-time uncertain nonlinear systems using a novel actor-critic-identifier (ACI) architecture to approximate the Hamilton-Jacobi-Bellman equation.