Behavioral Refinement via Interpolant-based Policy Diffusion

arXiv:2402.16075v1 Announce Type: new
Abstract: 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 …

abstract agents artificial arxiv behavior cs.ai cs.lg cs.ro diffusion diffusion models imitation learning learn multimodal noise performance policy standard tasks type via