sequential decision making

DataFunSummit

Mar 5, 2023 · Artificial Intelligence

Data‑Driven Decision Optimization: Challenges and Advances in Offline Reinforcement Learning

This article reviews the practical challenges of applying data‑driven decision optimization in real‑world systems, explains the fundamentals of offline reinforcement learning, discusses recent algorithmic innovations such as policy‑constraint methods and the DOGE framework, and presents industrial case studies including power‑plant control and mixed offline‑online RL approaches.

Offline Reinforcement Learningdata-driven decisionindustrial AI

0 likes · 27 min read

Data‑Driven Decision Optimization: Challenges and Advances in Offline Reinforcement Learning

Architects Research Society

Oct 4, 2015 · Artificial Intelligence

Bayesian Thinking on Your Feet: Embedding Generative Models in Reinforcement Learning for Sequentially Revealed Data

This NSF‑funded project aims to develop algorithms that incrementally process partially observed data, integrating generative models with reinforcement‑learning policies to decide when to act, applied to simultaneous machine translation and quiz‑bowl style question answering.

Bayesian inferenceGenerative Modelsmachine translation

0 likes · 4 min read

Bayesian Thinking on Your Feet: Embedding Generative Models in Reinforcement Learning for Sequentially Revealed Data