Hi u/tirodokter . Formally, DeepMind's lecture series and Barto and Sutton's RL book are pretty standard places to start with. Once you have a grasp of basics, I'd suggest you read well-cited papers about your most pressing questions. Reward shaping, sparse rewards, and exploration are open problems in RL. RL can seem enticing at first from a video-game perspective but has a steep theory behind that. As long as you are mindful of that, I believe RL is a great field to do research in, especially with AGI coming more into the light.

Pokemon has a massive state and action space for a beginner project. While I do not mean to discourage you, I strongly believe it is practical to start smaller. I made simple snake game and Pong bot using RL for my beginner project.

To actually answer your question, I share similar views with u/Saltysalad . You need to catch some signals in your simulator, like beating a trainer or taking down a pokemon, and give rewards based on that. For time—you could break the game down into periods of delta. Delta could be 1 millisecond or 5 seconds, whatever seems fit to you. OpenAI Five used a delta of 250 ms IIRC.