Don't Start from Scratch: Behavioral Refinement via Interpolant-based Policy Diffusion

Understand

Imitation learning empowers artificial agents to mimic behavior by learning from demonstrations.

• Recently, diffusion models, which have the ability to model high-dimensional and multimodal distributions, have shown impressive performance on imitation learning tasks.
• These models learn to shape a policy by diffusing actions (or states) from standard Gaussian noise.
• However, the target policy to be learned is often significantly different from Gaussian and this mismatch can result in poor performance when using a small number of diffusion steps (to improve inference speed) and under limited data.