Can PPO learn through “Imagination” similar to Dreamer?

Hi everyone,

I’ve been diving into the Dreamer paper recently, and I found the concept of learning a policy through “imagination”(within a latent world model) absolutely fascinating.

This got me wondering: Can the PPO (Proximal Policy Optimization) algorithm also be trained through imagination?

Specifically, instead of interacting with a real environment, could we plug PPO into a learned world model to update its policy? I’d love to hear your thoughts on the technical feasibility or if there are any existing papers that have explored this.

Thanks!