Sample-efficient Reinforcement Learning Representation Learning with Curiosity Contrastive Forward Dynamics Model
Thanh Nguyen,Tung M. Luu,Thang Vu,Chang D. Yoo,Thanh Nguyen,Tung M. Luu,Thang Vu,Chang D. Yoo
Developing an agent in reinforcement learning (RL) that is capable of performing complex control tasks directly from high-dimensional observation such as raw pixels is a challenge as efforts still need to be made towards improving sample efficiency and generalization of RL algorithm. This paper considers a learning framework for a Curiosity Contrastive Forward Dynamics Model (CCFDM) to achieve a m...
