18 citations · 31 across the 6 of their papers we have counts for
14 papers
Generative Planning for Temporally Coordinated Exploration in Reinforcement Learning
Haichao Zhang, Wei Xu, Haonan Yu
Standard model-free reinforcement learning algorithms optimize a policy that generates the action to be taken in the current time step in order to maximize expected future return.…
Do You Need the Entropy Reward (in Practice)?
Haonan Yu, Haichao Zhang, Wei Xu
Maximum entropy (MaxEnt) RL maximizes a combination of the original task reward and an entropy reward. It is believed that the regularization imposed by entropy, on both policy imp…
TAAC: Temporally Abstract Actor-Critic for Continuous Control
Haonan Yu, Wei Xu, Haichao Zhang
We present temporally abstract actor-critic (TAAC), a simple but effective off-policy RL algorithm that incorporates closed-loop temporal abstraction into the actor-critic framewor…
MetaView: Few-shot Active Object Recognition
Wei Wei, Haonan Yu, Haichao Zhang +2
In robot sensing scenarios, instead of passively utilizing human captured views, an agent should be able to actively choose informative viewpoints of a 3D object as discriminative…
Why Build an Assistant in Minecraft?
Arthur Szlam, Jonathan Gray, Kavya Srinet +11
In this document we describe a rationale for a research program aimed at building an open "assistant" in the game Minecraft, in order to make progress on the problems of natural la…
CraftAssist: A Framework for Dialogue-enabled Interactive Agents
Jonathan Gray, Kavya Srinet, Yacine Jernite +6
This paper describes an implementation of a bot assistant in Minecraft, and the tools and platform allowing players to interact with the bot and to record those interactions. The p…