2 citations · 2 across the 9 of their papers we have counts for
4 papers · 1 filter
Learning to Assist Humans without Inferring Rewards
Vivek Myers, Evan Ellis, Sergey Levine +2
Assistive agents should make humans' lives easier. Classically, such assistance is studied through the lens of inverse reinforcement learning, where an assistive agent (e.g., a cha…
Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitation
Vivek Myers, Bill Chunyuan Zheng, Oier Mees +2
Learned language-conditioned robot policies often struggle to effectively adapt to new real-world tasks even when pre-trained across a diverse set of instructions. We propose a nov…
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
Vivek Myers, Chongyi Zheng, Anca Dragan +2
Temporal distances lie at the heart of many algorithms for planning, control, and reinforcement learning that involve reaching goals, allowing one to estimate the transit time betw…
Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference
Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov +1
Given time series data, how can we answer questions like "what will happen in the future?" and "how did we get here?" These sorts of probabilistic inference questions are challengi…