Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore cutting-edge research on flexible behavior synthesis in this 40-minute presentation by MIT EECS PhD student Yilun Du. Delve into the innovative approach of planning with diffusion for generating adaptive trajectories and behaviors. Learn about neural networks combined with trajectory optimization, generative modeling for planning, and compositional trajectory generation. Discover the Diffuser model's capabilities in variable-length predictions and flexible behavior synthesis through distribution composition. Examine advanced techniques such as goal planning through inpainting, test-time cost specification, and offline reinforcement learning with value guidance. Gain insights into the application of test-time cost functions and their impact on behavior synthesis.