Reinforcement Learning w/ Keras OpenAI: Actor-Critic Models

Last time in our Keras/OpenAI tutorial, we discussed a very fundamental algorithm in reinforcement learning: the DQN. The Deep Q-Network is actually a fairly new advent that arrived on the seen only a couple years back, so it is quite incredible if you were able to understand and implement this algorithm having just gotten a start in the field. As with the original post, let's take a quick moment to appreciate how incredible results we achieved are: in a continuous output space scenario and starting with absolutely no knowledge on what "winning" entails, we were able to explore our environment and "complete" the trials. Put yourself in the situation of this simulation. This would essentially be like asking you to play a game, without a rulebook or specific endgoal, and demanding you to continue to play until you win (almost seems a bit cruel).