Decision Making Under Uncertainty

42 papers with code • 0 benchmarks • 2 datasets

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Latest papers with no code

A Neuro-Symbolic Approach to Multi-Agent RL for Interpretability and Probabilistic Decision Making

no code yet • 21 Feb 2024

To enable decision-making under uncertainty and partial observability, we developed a novel probabilistic neuro-symbolic framework, Probabilistic Logical Neural Networks (PLNN), which combines the capabilities of logical reasoning with probabilistic graphical models.

Probability Tools for Sequential Random Projection

no code yet • 16 Feb 2024

We introduce the first probabilistic framework tailored for sequential random projection, an approach rooted in the challenges of sequential decision-making under uncertainty.

Thompson Sampling in Partially Observable Contextual Bandits

no code yet • 15 Feb 2024

Accordingly, a fundamental problem is that of balancing exploration (i. e., pulling different arms to learn their parameters), versus exploitation (i. e., pulling the best arms to gain reward).

Second Order Methods for Bandit Optimization and Control

no code yet • 14 Feb 2024

We show that our algorithm achieves optimal (in terms of horizon) regret bounds for a large class of convex functions that we call $\kappa$-convex.

Stochastic COLREGs Evaluation for Safe Navigation under Uncertainty

no code yet • 8 Feb 2024

This article considers decision making under uncertainty and suggests a novel method for probabilistic interpretation of vessel encounters that is explainable and provides a measure of uncertainty in the evaluation.

DeLLMa: A Framework for Decision Making Under Uncertainty with Large Language Models

no code yet • 4 Feb 2024

Large language models (LLMs) are increasingly used across society, including in domains like business, engineering, and medicine.

Partially Law-Invariant Risk Measures

no code yet • 30 Jan 2024

A notion of strong partial law invariance is introduced, allowing for a representation formula akin to the classical one.

High-dimensional forecasting with known knowns and known unknowns

no code yet • 26 Jan 2024

Forecasts play a central role in decision making under uncertainty.

Probabilistic Demand Forecasting with Graph Neural Networks

no code yet • 23 Jan 2024

We also show that our approach produces article embeddings that encode article similarity and demand dynamics and are useful for other downstream business tasks beyond forecasting.

"Bayesian anchoring" and the fourfold pattern of risk attitudes

no code yet • 13 Jan 2024

Experiments on decision making under uncertainty are known to display a classical pattern of risk aversion and risk seeking referred to as "fourfold pattern" (or "reflection effect") , but recent experiments varying the speed and order of mental processing have brought to light a more nuanced phenomenology.