
Optimal Learning for Sequential Decisions in Laboratory Experimentation
The process of discovery in the physical, biological and medical science...
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On State Variables, Bandit Problems and POMDPs
State variables are easily the most subtle dimension of sequential decis...
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Zerothorder Stochastic Compositional Algorithms for RiskAware Learning
We present FreeMESSAGEp, the first zerothorder algorithm for convex me...
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From Reinforcement Learning to Optimal Control: A unified framework for sequential decisions
There are over 15 distinct communities that work in the general area of ...
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Approximate Dynamic Programming for Planning a RideSharing System using Autonomous Fleets of Electric Vehicles
Within a decade, almost every major auto company, along with fleet opera...
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Recursive Optimization of Convex Risk Measures: MeanSemideviation Models
We develop and analyze stochastic subgradient methods for optimizing a n...
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Monte Carlo Tree Search with Sampled Information Relaxation Dual Bounds
Monte Carlo Tree Search (MCTS), most famously used in gameplay artifici...
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RiskAverse Approximate Dynamic Programming with QuantileBased Risk Measures
In this paper, we consider a finitehorizon Markov decision process (MDP...
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A Knowledge Gradient Policy for Sequencing Experiments to Identify the Structure of RNA Molecules Using a Sparse Additive Belief Model
We present a sparse knowledge gradient (SpKG) algorithm for adaptively s...
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A New Optimal Stepsize For Approximate Dynamic Programming
Approximate dynamic programming (ADP) has proven itself in a wide range ...
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Dirichlet Process Mixtures of Generalized Linear Models
We propose Dirichlet Process mixtures of Generalized Linear Models (DPG...
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Warren B. Powell
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