aureliantactics

Paper Implementation of ‘Using Unity to Help Solve Intelligence:’ Code Walkthrough

Paper Implementation: Using Unity to Help Solve Intelligence

Implementing DQNClipped and DQNReg with Stable Baselines

BCQ with a GAN

There’s been a lot of interesting stuff in the field of batch Reinforcement Learning (aka offline RL) since I wrote about…

Implementing Unity Machine Learning into an Existing Game: Gridworld in Aurelian Tactics

Setting Up Unity ML Agents with Ray and Stable Baselines

Batch-Constrained Deep Q Learning in TensorFlow

Learn Reinforcement Learning with TensorFlow and TRFL

Trust Region-Guided Proximal Policy Optimization

Custom Models with Baselines: IMPALA CNN, CNNs with Features, and Contra 3 Hard Mode

Beating Contra III on Easy Mode with Reinforcement Learning — Part 3 Discussion

Beating Contra III on Easy Mode with Reinforcement Learning — Part 2: Experiment

Beating Easy Mode on Contra III with Reinforcement Learning — Part 1: Introduction

Basic TRFL Usage: Target Network Updating

Continuing my exploration of TRFL — a Reinforcement…

Basic TRFL Usage: Q-Learning and Double Q-Learning

Retro Gym with Baselines: 4 Basic Usage Tips

A short summary and code example followed by explanations.

Tensorflow Implementation of TD3 in OpenAI Baselines

When I’m looking for new research papers to read, it’s often hard to tell what is worth reading. How reproducible are the results? Will this paper actually have a lasting impact in the field of Reinforcement Learning (RL)? With those…

Location CNN and Pygame Learning Environment in Ray

Two recent papers came out that discussed the same issue: how to utilize location information in Convolutional Neural Networks. Basic CNNs are useful for their ability to pick out the similar objects at different locations in the image…