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b'Today we\\u2019re joined by Gokul Swamy, a Ph.D. Student at the Robotics Institute at Carnegie Mellon University. In the final conversation of our ICML 2023 series, we sat down with Gokul to discuss his accepted papers at the event, leading off with \\u201cInverse Reinforcement Learning without Reinforcement Learning.\\u201d In this paper, Gokul explores the challenges and benefits of inverse reinforcement learning, and the potential and advantages it holds for various applications. Next up, we explore the \\u201cComplementing a Policy with a Different Observation Space\\u201d paper which applies causal inference techniques to accurately estimate sampling balance and make decisions based on limited observed features. Finally, we touched on \\u201cLearning Shared Safety Constraints from Multi-task Demonstrations\\u201d which centers on learning safety constraints from demonstrations using the inverse reinforcement learning approach.\\n\\nThe complete show notes for this episode can be found at twimlai.com/go/643.'