video1.0<iframe src="https://www.loom.com/embed/7dda14bfc31b458eaa472a8d34e352c4" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/7dda14bfc31b458eaa472a8d34e352c4-9b69bf374cc95e7e.gif78.148In this video, I discuss our efforts to create a robust environment for a new poker data set developed by Yoni, who is an expert in a specific poker format. We have implemented custom reward functions to improve our model's performance, focusing on action matching and bet sizing. I encourage you to subscribe and engage with the content as we refine this environment. Your feedback will be invaluable as we move forward.