154 citations · 1k across the 49 of their papers we have counts for
13 papers · 1 filter
A Framework for Time-Consistent, Risk-Sensitive Model Predictive Control: Theory and Algorithms
Sumeet Singh, Yin-Lam Chow, Anirudha Majumdar +1
In this paper we present a framework for risk-sensitive model predictive control (MPC) of linear systems affected by stochastic multiplicative uncertainty. Our key innovation is to…
Risk Aversion in Finite Markov Decision Processes Using Total Cost Criteria and Average Value at Risk
Stefano Carpin, Yin-Lam Chow, Marco Pavone
In this paper we present an algorithm to compute risk averse policies in Markov Decision Processes (MDP) when the total cost criterion is used together with the average value at ri…
A Framework for Time-Consistent, Risk-Averse Model Predictive Control: Theory and Algorithms
Yin-Lam Chow, Marco Pavone
In this paper we present a framework for risk-averse model predictive control (MPC) of linear systems affected by multiplicative uncertainty. Our key innovation is to consider time…
Stochastic Optimal Control With Dynamic, Time-Consistent Risk Constraints
Yin-Lam Chow, Marco Pavone
In this paper we present a dynamic programing approach to stochastic optimal control problems with dynamic, time-consistent risk constraints. Constrained stochastic optimal control…
Robust Policy Optimization with Baseline Guarantees
Yinlam Chow, Marek Petrik, Mohammad Ghavamzadeh
Our goal is to compute a policy that guarantees improved return over a baseline policy even when the available MDP model is inaccurate. The inaccurate model may be constructed, for…
Control of Generalized Energy Storage Networks
Junjie Qin, Yinlam Chow, Jiyan Yang +1
The integration of intermittent and volatile renewable energy resources requires increased flexibility in the operation of the electric grid. Storage, broadly speaking, provides th…
A Time Consistent Formulation of Risk Constrained Stochastic Optimal Control
Yinlam Chow, Marco Pavone
Time-consistency is an essential requirement in risk sensitive optimal control problems to make rational decisions. An optimization problem is time consistent if its solution polic…
Weighted SGD for Regression with Randomized Preconditioning
Jiyan Yang, Yin-Lam Chow, Christopher Ré +1
In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and dat…
A Uniform-grid Discretization Algorithm for Stochastic Control with Risk Constraints
Yin-Lam Chow, Marco Pavone
In this paper, we present a discretization algorithm for finite horizon risk constrained dynamic programming algorithm in [Chow_Pavone_13]. Although in a theoretical standpoint, Be…
Weighted Difference Approximation of Value Functions for Slow-Discounting Markov Decision Processes
Yin-Lam Chow, Junjie Qin
Processes (MDPs) often require frequent decision making, that is, taking an action every microsecond, second, or minute. Infinite horizon discount reward formulation is still relev…
Constrained Stochastic Optimal Control with a Baseline Performance Guarantee
Yinlam Chow, Mohammad Ghavamzadeh
In this paper, we show how a simulated Markov decision process (MDP) built by the so-called \emph{baseline} policies, can be used to compute a different policy, namely the \emph{si…
Distributed Online Modified Greedy Algorithm for Networked Storage Operation under Uncertainty
Junjie Qin, Yinlam Chow, Jiyan Yang +1
The integration of intermittent and stochastic renewable energy resources requires increased flexibility in the operation of the electric grid. Storage, broadly speaking, provides…
Online Modified Greedy Algorithm for Storage Control under Uncertainty
Junjie Qin, Yinlam Chow, Jiyan Yang +1
This paper studies the general problem of operating energy storage under uncertainty. Two fundamental sources of uncertainty are considered, namely the uncertainty in the unexpecte…