This paper studies the impact of imperfect information in online control with adversarial disturbances. In particular, we consider both delayed state feedback and inexact predictions of future disturbances. We introduce a greedy, myopic policy that yields a constant competitive ratio against the offline optimal policy with delayed feedback and inexact predictions. A special case of our result is a constant competitive policy for the case of exact predictions and no delay, a previously open problem. We also analyze the fundamental limits of online control with limited information by showing that our competitive ratio bounds for the greedy, myopic policy in the adversarial setting match (up to lower-order terms) lower bounds in the stochastic...
We study the power of different types of adaptive (nonoblivious) adversaries in the setting of predi...
The main contribution is the application of a zero-sum game-theoretic framework and performance-meas...
Modern control systems can be viewed as interconnections of spatially distributed multiple subsystem...
This paper studies the impact of imperfect information in online control with adversarial disturbanc...
Recently a line of work has shown the applicability of tools from online optimization for control, l...
We study the impact of predictions in online Linear Quadratic Regulator control with both stochastic...
For many online problems disappointing lower bounds on the achiev-able competitive ratio have been s...
We consider the fundamental problem of online control of a linear dynamical system from two differen...
International audienceWe consider a model of game-theoretic learning based on online mirro...
Most on-line analysis assumes that, at each time step, all relevant information up to that time step...
AbstractMost on-line analysis assumes that, at each time step, all relevant information up to that t...
We study fully dynamic online selection problems in an adversarial/stochastic setting that includes ...
We extend the folk theorem of repeated games to two settings in which players ’ information about ot...
International audienceWe consider a multi-criteria control problem that arises in a delay tolerant n...
This thesis poses a general model for optimal control subject to information constraint, motivated i...
We study the power of different types of adaptive (nonoblivious) adversaries in the setting of predi...
The main contribution is the application of a zero-sum game-theoretic framework and performance-meas...
Modern control systems can be viewed as interconnections of spatially distributed multiple subsystem...
This paper studies the impact of imperfect information in online control with adversarial disturbanc...
Recently a line of work has shown the applicability of tools from online optimization for control, l...
We study the impact of predictions in online Linear Quadratic Regulator control with both stochastic...
For many online problems disappointing lower bounds on the achiev-able competitive ratio have been s...
We consider the fundamental problem of online control of a linear dynamical system from two differen...
International audienceWe consider a model of game-theoretic learning based on online mirro...
Most on-line analysis assumes that, at each time step, all relevant information up to that time step...
AbstractMost on-line analysis assumes that, at each time step, all relevant information up to that t...
We study fully dynamic online selection problems in an adversarial/stochastic setting that includes ...
We extend the folk theorem of repeated games to two settings in which players ’ information about ot...
International audienceWe consider a multi-criteria control problem that arises in a delay tolerant n...
This thesis poses a general model for optimal control subject to information constraint, motivated i...
We study the power of different types of adaptive (nonoblivious) adversaries in the setting of predi...
The main contribution is the application of a zero-sum game-theoretic framework and performance-meas...
Modern control systems can be viewed as interconnections of spatially distributed multiple subsystem...