Decision Making Under Uncertainty
43 papers with code • 0 benchmarks • 2 datasets
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High-dimensional forecasting with known knowns and known unknowns
Forecasts play a central role in decision making under uncertainty.
Decision Making in Non-Stationary Environments with Policy-Augmented Search
In this paper, we introduce \textit{Policy-Augmented Monte Carlo tree search} (PA-MCTS), which combines action-value estimates from an out-of-date policy with an online search using an up-to-date model of the environment.
Explaining Predictive Uncertainty with Information Theoretic Shapley Values
Researchers in explainable artificial intelligence have developed numerous methods for helping users understand the predictions of complex supervised learning models.
Measurement Simplification in ρ-POMDP with Performance Guarantees
In both cases we show a significant speed-up in planning with performance guarantees.
Simple Modification of the Upper Confidence Bound Algorithm by Generalized Weighted Averages
In preliminary experiments, we investigated the optimal parameters of a simple generalized UCB1 (G-UCB1), prepared for comparison and GWA-UCB1, in a stochastic MAB problem with two arms.
Uncertainty Quantification for Image-based Traffic Prediction across Cities
We compare two epistemic and two aleatoric UQ methods on both temporal and spatio-temporal transfer tasks, and find that meaningful uncertainty estimates can be recovered.
Gaussian Latent Representations for Uncertainty Estimation using Mahalanobis Distance in Deep Classifiers
Recent works show that the data distribution in a network's latent space is useful for estimating classification uncertainty and detecting Out-of-distribution (OOD) samples.
Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs
Inverse optimal control can be used to characterize behavior in sequential decision-making tasks.
Minimax-Bayes Reinforcement Learning
While the Bayesian decision-theoretic framework offers an elegant solution to the problem of decision making under uncertainty, one question is how to appropriately select the prior distribution.
Safe and Adaptive Decision-Making for Optimization of Safety-Critical Systems: The ARTEO Algorithm
We consider the problem of decision-making under uncertainty in an environment with safety constraints.