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RL Weekly 31: How Agents Play Hide and Seek, Attraction-Repulsion Actor Critic, and Efficient Learning from Demonstrations

RL Weekly 31: How Agents Play Hide and Seek, Attraction-Repulsion Actor Critic, and Efficient Learning from Demonstrations

In this issue, we look at OpenAI's work on multi-agent hide and seek and the behaviors that emerge. We also look at Mila's population-based exploration...

Reinforcement Learning Papers Accepted to NeurIPS 2019

Reinforcement Learning Papers Accepted to NeurIPS 2019

I have compiled a list of 184 reinforcement learning papers accepted to NeurIPS 2019.

RL Weekly 30: Learning State and Action Embeddings, a New Framework for RL in Games, and an Interactive Variant of Question Answering

RL Weekly 30: Learning State and Action Embeddings, a New Framework for RL in Games, and an Interactive Variant of Question Answering

In this issue, we look at a representation learning method to train state and action embeddings paired with TD3. We also look at a new...

githubtocolab: Open GitHub Jupyter Notebooks in Colab!

githubtocolab: Open GitHub Jupyter Notebooks in Colab!

GitHub is a great place to host jupyter notebooks, and Colab is a great place to run jupyter notebooks. Use githubtocolab.com to instantly open jupyter...

RL Weekly 29: The Behaviors and Superstitions of RL, and How Deep RL Compares with the Best Humans in Atari

RL Weekly 29: The Behaviors and Superstitions of RL, and How Deep RL Compares with the Best Humans in Atari

In this issue, we look at reinforcement learning from a wider perspective. We look at new environments and experiments that are designed to test and...

RL Weekly 28: Free-Lunch Saliency and Hierarchical RL with Behavior Cloning

RL Weekly 28: Free-Lunch Saliency and Hierarchical RL with Behavior Cloning

This week, we first look at Free-Lunch Saliency, a built-in interpretability module that does not deteriorate performance. Then, we look at HRL-BC, a combination of...