Deep reinforcement learning is a powerful technique for creating effective decision-making systems, but its complexity has hindered widespread adoption. Despite the perceived cost of RL, a wide range of interesting applications are already feasible with current techniques. The main barrier to broader use of RL is now the lack of accessible tooling and infrastructure. In this blog post, I introduce the Entity Neural Network (ENN) project , a set of libraries designed to simplify the process of applying RL to
The rapid progress in deep reinforcement learning (RL) over the last few years holds the promise of fixing the shortcomings of computer opponents in video games and of unlocking entirely new regions in game design space. However, the exorbitant engineering effort and hardware investments required to train neural networks that master complex real-time strategy games might lead to the impression that the commercial viability of deep RL is still far in the future. To the contrary, I will argue in Part 1 of thi
Within these pages are recorded my attempts to wield the highest arcane art and conjure minds that play the game of CodeCraft .