Aswin Ramachandran

Mastering the Labyrinth Game: Efficient Multimodal Reinforcement Learning with Selective Reconstruction

In previous work, model-based reinforcement learning was applied to a real-world labyrinth game to demonstrate sample-efficient learning using world models. In this paper, we further enhance sample efficiency and autonomy by introducing selective reconstruction: instead of reconstructing the full vi