AI Paper Atlas

Research map / Reinforcement learning / Visual and representation RL

Contrastive Learning as Goal-Conditioned Reinforcement Learning

NeurIPS 2022 · Reinforcement learning › Visual and representation RL · approach: Graph search and compositional goals · 24 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use contrastive RL with goal relabeling instead of prior offline baselinesOffline goal-conditioned RL · D4RL AntMaze large-play-v2 and large-diverse-v2normalized score: 41.6 {( ±6.0)} vs 39.6; 49.3 {( ±6.3)} vs 47.5Helped
Increase the number of critics from 2 to 5 (ablation)Offline Contrastive RL + BC · D4RL AntMaze tasksnormalized score: 81.9 {( ±1.7)} -> 79.8 {( ±1.4)}; 75.4 {( ±3.5)} -> 77.6 {( ±2.8)}; 71.5 {( ±5.2)} -> 72.6 {( ±2.9)}; 72.5 {( ±2.8)} -> Mixed
Add filtering of relabeled trajectories based on commanded-versus-reached-goal likelihood (ablation)Contrastive RL (NCE) · Goal-conditioned RL taskssuccess rateHurt
Sample future states rather than random states as actor-loss goals (ablation)Contrastive RL (NCE) · Goal-conditioned RL taskssuccess rateHurt
Use a mixture of future goals and random goals for the actor loss (ablation)Contrastive RL (NCE) · Goal-conditioned RL taskssuccess rateMixed
Replace the NCE objective with the CPC objective (ablation)Contrastive RL · Goal-conditioned taskssuccess rateMixed
Replace NCE with C-learning (ablation)Contrastive RL · Goal-conditioned taskssuccess rateMixed
Combine the NCE objective with C-learning (ablation)Contrastive RL · Goal-conditioned taskssuccess rateHelped
Add image data augmentation and auxiliary representation losses to TD3+HER (ablation)TD3+HER · fetch reach and sawyer push image-based taskssuccess rateHelped
Use Contrastive RL (NCE) instead of TD3+HER with representation-learning additionsImage-based goal-conditioned RL · Image-based taskssuccess rateHelped
Normalize the final representation, add a final activation, or use a learnable temperature (ablation)Contrastive RL (NCE) · Goal-conditioned taskssuccess rateHurt
Use contrastive RL instead of a forward model as goal dimension increasessawyer push · Goal dimensions 4 through 7Euclidean distance to goalHelped

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy