14 citations · 135 across the 33 of their papers we have counts for
5 papers · 1 filter
Backward Approximate Dynamic Programming with Hidden Semi-Markov Stochastic Models in Energy Storage Optimization
Joseph L. Durante, Juliana Nascimento, Warren B. Powell
We consider an energy storage problem involving a wind farm with a forecasted power output, a stochastic load, an energy storage device, and a connection to the larger power grid w…
Optimal Learning for Sequential Decision Making for Expensive Cost Functions with Stochastic Binary Feedbacks
Yingfei Wang, Chu Wang, Warren Powell
We consider the problem of sequentially making decisions that are rewarded by "successes" and "failures" which can be predicted through an unknown relationship that depends on a pa…
MOLTE: a Modular Optimal Learning Testing Environment
Yingfei Wang, Warren Powell
We address the relative paucity of empirical testing of learning algorithms (of any type) by introducing a new public-domain, Modular, Optimal Learning Testing Environment (MOLTE)…
Monte Carlo Tree Search with Sampled Information Relaxation Dual Bounds
Daniel R. Jiang, Lina Al-Kanj, Warren B. Powell
Monte Carlo Tree Search (MCTS), most famously used in game-play artificial intelligence (e.g., the game of Go), is a well-known strategy for constructing approximate solutions to s…
Stochastic Optimization with Parametric Cost Function Approximations
Raymond T. Perkins, Warren B. Powell
A widely used heuristic for solving stochastic optimization problems is to use a deterministic rolling horizon procedure, which has been modified to handle uncertainty (e.g. buffer…