BROADCASTS.com

b"Take our survey at twimlai.com/survey21!\\n\\nToday we\\u2019re joined by Tim Rockt\\xe4schel, a research scientist at Facebook AI Research and an associate professor at University College London (UCL).\\xa0\\n\\nTim\\u2019s work focuses on training RL agents in simulated environments, with the goal of these agents being able to generalize to novel situations. Typically, this is done in environments like OpenAI Gym, MuJuCo, or even using Atari games, but these all come with constraints. In Tim\\u2019s approach, he utilizes a game called NetHack, which is much more rich and complex than the aforementioned environments.\\xa0\\xa0\\n\\nIn our conversation with Tim, we explore the ins and outs of using NetHack as a training environment, including how much control a user has when generating each individual game and the challenges he's faced when deploying the agents. We also discuss his work on MiniHack, an environment creation framework and suite of tasks that are based on NetHack, and future directions for this research.\\n\\nThe complete show notes for this episode can be found at twimlai.com/go/527."