324 citations · 2.8k across the 66 of their papers we have counts for
7 papers · 1 filter
Foundation Models for Decision Making: Problems, Methods, and Opportunities
Sherry Yang, Ofir Nachum, Yilun Du +3
Foundation models pretrained on diverse data at scale have demonstrated extraordinary capabilities in a wide range of vision and language tasks. When such models are deployed in re…
Learning Universal Policies via Text-Guided Video Generation
Yilun Du, Mengjiao Yang, Bo Dai +5
A goal of artificial intelligence is to construct an agent that can solve a wide variety of tasks. Recent progress in text-guided image synthesis has yielded models with an impress…
Multi-Game Decision Transformers
Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang +8
A longstanding goal of the field of AI is a method for learning a highly capable, generalist agent from diverse experience. In the subfields of vision and language, this was largel…
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning
Ofir Nachum, Shixiang Gu, Honglak Lee +1
We study the problem of representation learning in goal-conditioned hierarchical reinforcement learning. In such hierarchical structures, a higher-level controller solves tasks by…
Path Consistency Learning in Tsallis Entropy Regularized MDPs
Ofir Nachum, Yinlam Chow, Mohammad Ghavamzadeh
We study the sparse entropy-regularized reinforcement learning (ERL) problem in which the entropy term is a special form of the Tsallis entropy. The optimal policy of this formulat…
Trust-PCL: An Off-Policy Trust Region Method for Continuous Control
Ofir Nachum, Mohammad Norouzi, Kelvin Xu +1
Trust region methods, such as TRPO, are often used to stabilize policy optimization algorithms in reinforcement learning (RL). While current trust region strategies are effective f…
Bridging the Gap Between Value and Policy Based Reinforcement Learning
Ofir Nachum, Mohammad Norouzi, Kelvin Xu +1
We establish a new connection between value and policy based reinforcement learning (RL) based on a relationship between softmax temporal value consistency and policy optimality un…