Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future

Understand

In model-based reinforcement learning, the agent interleaves between model learning and planning.

• These two components are inextricably intertwined.
• If the model is not able to provide sensible long-term prediction, the executed planner would exploit model flaws, which can yield catastrophic failures.
• This paper focuses on building a model that reasons about the long-term future and demonstrates how to use this for efficient planning and exploration.