Causally Correct Partial Models for Reinforcement Learning

Understand

In reinforcement learning, we can learn a model of future observations and rewards, and use it to plan the agent's next actions.

• However, jointly modeling future observations can be computationally expensive or even intractable if the observations are high-dimensional (e.g.
• images).
• For this reason, previous works have considered partial models, which model only part of the observation.