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#Offline Reinforcement Learning

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University of Central Florida

CAP6412 - Final Project Presentations - Lecture 27

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Final project presentations showcasing innovative approaches in video action recognition, offline reinforcement learning, and decision transformer encoders, with discussions on methodologies, results, and implications.
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16 Lesons
1 hour 55 minutes
On-Demand
Free-Video
Simons Institute

Reinforcement Learning

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Explore reinforcement learning's foundations, applications, and advanced concepts, including Q-learning, exploration-exploitation trade-offs, and instance-optimality in policy evaluation.
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17 Lesons
31 minutes
On-Demand
Free-Video
Yannic Kilcher

NeurIPS 2023 Poster Session 1 - Adversarial Patches, Continual Learning, and Reinforcement Learning

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Explore cutting-edge AI research from NeurIPS 2023, covering adversarial patches, continual learning, neural network inference, and offline reinforcement learning.
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1 Lesons
19 minutes
On-Demand
Free-Video
Yannic Kilcher

Can Wikipedia Help Offline Reinforcement Learning - Author Interview

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Exploring the potential of pre-trained language models in offline reinforcement learning, discussing experimental results, model performance, and future directions for leveraging sequence modeling techniques in RL tasks.
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14 Lesons
45 minutes
On-Demand
Free-Video
Yannic Kilcher

Can Wikipedia Help Offline Reinforcement Learning? - Paper Explained

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Exploring how pre-training on Wikipedia improves offline reinforcement learning models, enhancing performance, reducing parameters, and revealing connections between language and RL domains.
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8 Lesons
39 minutes
On-Demand
Free-Video
Yannic Kilcher

Decision Transformer - Reinforcement Learning via Sequence Modeling

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Explore how Decision Transformer reframes offline reinforcement learning as sequence modeling, leveraging Transformer architecture to generate optimal actions based on desired returns, past states, and actions.
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13 Lesons
57 minutes
On-Demand
Free-Video
Yannic Kilcher

Datasets for Data-Driven Reinforcement Learning

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Explore offline reinforcement learning benchmarks and datasets for evaluating algorithms in various settings, including safety-critical tasks and learning from expert demonstrations.
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1 Lesons
20 minutes
On-Demand
Free-Video
Pascal Poupart

Bayesian RL

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Explore Bayesian reinforcement learning techniques, including planning, sampling, and value iteration, to optimize decision-making in uncertain environments.
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12 Lesons
1 hour 22 minutes
On-Demand
Free-Video
Simons Institute

Offline Reinforcement Learning and Model-Based Optimization

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Explore offline reinforcement learning and model-based optimization techniques, focusing on data-driven approaches, Q-function lower bounds, and model inversion networks for automated decision-making.
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23 Lesons
34 minutes
On-Demand
Free-Video
Simons Institute

What Are the Statistical Limits of Offline Reinforcement Learning With Function Approximation?

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Explore statistical limitations in offline reinforcement learning with function approximation, covering realizability, coverage, policy evaluation, and practical considerations.
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26 Lesons
55 minutes
On-Demand
Free-Video
Simons Institute

Discussion - Offline Reinforcement Learning

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Explore offline reinforcement learning, covering data sets, optimism under uncertainty, state coverage, and policy evaluation. Gain insights into pragmatic and conceptual approaches.
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23 Lesons
40 minutes
On-Demand
Free-Video
Simons Institute

Batch Offline Reinforcement Learning - Part 1

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Explore offline reinforcement learning theory, covering key concepts, challenges, and evaluation methods for developing AI systems using pre-collected data.
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18 Lesons
59 minutes
On-Demand
Free-Video
Simons Institute

Generalization and Robustness in Offline Reinforcement Learning

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Explore offline reinforcement learning for safety-critical applications, covering generalization, robustness, and imitation learning in large-scale settings with rich function approximation.
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19 Lesons
54 minutes
On-Demand
Free-Video
SK AI SUMMIT 2024

Offline Reinforcement Learning for Process Control - CDU Air Fan Cooler Control Application

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Discover how offline reinforcement learning can optimize crude distillation unit control through historical data analysis, avoiding costly trial-and-error approaches in industrial process control systems.
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1 Lesons
21 minutes
On-Demand
Free-Video