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Optimal Learning for Sequential Decisions in Laboratory Experimentation
The process of discovery in the physical, biological and medical science...
04/11/2020 ∙ by Kris Reyes, et al. ∙
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On State Variables, Bandit Problems and POMDPs
State variables are easily the most subtle dimension of sequential decis...
02/14/2020 ∙ by Warren B. Powell, et al. ∙
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Zeroth-order Stochastic Compositional Algorithms for Risk-Aware Learning
We present Free-MESSAGEp, the first zeroth-order algorithm for convex me...
12/19/2019 ∙ by Dionysios S. Kalogerias, et al. ∙
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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 ...
12/07/2019 ∙ by Warren B. Powell, et al. ∙
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Approximate Dynamic Programming for Planning a Ride-Sharing System using Autonomous Fleets of Electric Vehicles
Within a decade, almost every major auto company, along with fleet opera...
10/18/2018 ∙ by Lina Al-Kanj, et al. ∙
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Recursive Optimization of Convex Risk Measures: Mean-Semideviation Models
We develop and analyze stochastic subgradient methods for optimizing a n...
04/02/2018 ∙ by Dionysios S. Kalogerias, et al. ∙
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Monte Carlo Tree Search with Sampled Information Relaxation Dual Bounds
Monte Carlo Tree Search (MCTS), most famously used in game-play artifici...
04/20/2017 ∙ by Daniel R. Jiang, et al. ∙
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Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures
In this paper, we consider a finite-horizon Markov decision process (MDP...
09/07/2015 ∙ by Daniel R. Jiang, et al. ∙
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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...
08/06/2015 ∙ by Yan Li, et al. ∙
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A New Optimal Stepsize For Approximate Dynamic Programming
Approximate dynamic programming (ADP) has proven itself in a wide range ...
07/10/2014 ∙ by Ilya O. Ryzhov, et al. ∙
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Dirichlet Process Mixtures of Generalized Linear Models
We propose Dirichlet Process mixtures of Generalized Linear Models (DP-G...
09/28/2009 ∙ by Lauren A. Hannah, et al. ∙
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