4 citations · 6 across the 6 of their papers we have counts for
11 papers · 1 filter
Robustness to Modeling Errors in Risk-Sensitive Markov Decision Problems with Markov Risk Measures
Shiping Shao, Abhishek Gupta, William B. Haskell
We consider risk-sensitive Markov decision processes (MDPs), where the MDP model is influenced by a parameter which takes values in a compact metric space. We identify sufficient c…
A dynamic analytic method for risk-aware controlled martingale problems
Jukka Isohätälä, William B. Haskell
We present a new, tractable method for solving and analyzing risk-aware control problems over finite and infinite, discounted time-horizons where the dynamics of the controlled pro…
A Randomized Nonlinear Rescaling Method in Large-Scale Constrained Convex Optimization
Bo Wei, William B. Haskell, Sixiang Zhao
We propose a new randomized algorithm for solving convex optimization problems that have a large number of constraints (with high probability). Existing methods like interior-point…
A Flexible Multi-Facility Capacity Expansion Problem with Risk Aversion
Sixiang Zhao, William B. Haskell, Michel-Alexandre Cardin
This paper studies flexible multi-facility capacity expansion with risk aversion. In this setting, the decision maker can periodically expand the capacity of facilities given obser…
A Multi-Level Simulation Optimization Approach for Quantile Functions
Songhao Wang, Szu Hui Ng, William Benjamin Haskell
Quantile is a popular performance measure for a stochastic system to evaluate its variability and risk. To reduce the risk, selecting the actions that minimize the tail quantiles o…
An Accelerated Fitted Value Iteration Algorithm for MDPs with Finite and Vector-Valued Action Space
Sixiang Zhao, William B. Haskell, Michel-Alexandre Cardin
This paper studies an accelerated fitted value iteration (FVI) algorithm to solve high-dimensional Markov decision processes (MDPs). FVI is an approximate dynamic programming algor…