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Simons Institute

Mixed Autonomy Traffic: A Reinforcement Learning Perspective

Simons Institute

Learning Exploration Strategies with Meta-Reinforcement Learning

Simons Institute

MOPO - Model-Based Offline Policy Optimization

Alan Turing Institute

Gaming for Military Precision Decisions - Simon Lucas

USENIX

GMI-DRL - Empowering Multi-GPU DRL with Adaptive-Grained Parallelism

Montreal Robotics

Robot Learning 2025: Foundational Models for Robotics and Scaling DeepRL

Cooperative AI Foundation

Modelling Humans with Neural Networks for Behavioural Mechanism Design

Montreal Robotics

Scaling Deep Q-Learning - Part 2

Eclipse Foundation

Challenges in Reward Design for Reinforcement Learning-based Traffic Signal Control - An Investigation Using CO2 Emission Objective

Montreal Robotics

Scaling Continuous Deep QLearning - Part 1

Black Hat

CodeCloak: A DRL-Based Method for Mitigating Code Leakage by LLM Code Assistants

Deep Reinforcement Learning for Object Tracking

TensorFlow

TensorFlow and Deep Reinforcement Learning, Without a PhD - Google I/O '18

GDC

Successfully Use Deep Reinforcement Learning in Testing and NPC Development

Serrano.Academy

A Friendly Introduction to Deep Reinforcement Learning, Q-Networks and Policy Gradients

Deep Reinforcement Learning Courses and Certifications

Mixed Autonomy Traffic: A Reinforcement Learning Perspective

Learning Exploration Strategies with Meta-Reinforcement Learning

MOPO - Model-Based Offline Policy Optimization

Gaming for Military Precision Decisions - Simon Lucas

GMI-DRL - Empowering Multi-GPU DRL with Adaptive-Grained Parallelism

Robot Learning 2025: Foundational Models for Robotics and Scaling DeepRL

Modelling Humans with Neural Networks for Behavioural Mechanism Design

Scaling Deep Q-Learning - Part 2

Challenges in Reward Design for Reinforcement Learning-based Traffic Signal Control - An Investigation Using CO2 Emission Objective

Scaling Continuous Deep QLearning - Part 1

CodeCloak: A DRL-Based Method for Mitigating Code Leakage by LLM Code Assistants

Deep Reinforcement Learning for Object Tracking

TensorFlow and Deep Reinforcement Learning, Without a PhD - Google I/O '18

Successfully Use Deep Reinforcement Learning in Testing and NPC Development

A Friendly Introduction to Deep Reinforcement Learning, Q-Networks and Policy Gradients