275 citations · 437 across the 32 of their papers we have counts for
4 papers · 1 filter
Gradient Boosting Reinforcement Learning
Benjamin Fuhrer, Chen Tessler, Gal Dalal
We present Gradient Boosting Reinforcement Learning (GBRL), a framework that adapts the strengths of gradient boosting trees (GBT) to reinforcement learning (RL) tasks. While neura…
PlaMo: Plan and Move in Rich 3D Physical Environments
Assaf Hallak, Gal Dalal, Chen Tessler +3
Controlling humanoids in complex physically simulated worlds is a long-standing challenge with numerous applications in gaming, simulation, and visual content creation. In our setu…
Tree Search-Based Policy Optimization under Stochastic Execution Delay
David Valensi, Esther Derman, Shie Mannor +1
The standard formulation of Markov decision processes (MDPs) assumes that the agent's decisions are executed immediately. However, in numerous realistic applications such as roboti…
Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization
Yihan Du, Anna Winnicki, Gal Dalal +2
Reinforcement Learning from Human Feedback (RLHF) has achieved impressive empirical successes while relying on a small amount of human feedback. However, there is limited theoretic…