Learning Multiple Timescales for Goal-Conditioned Reinforcement Learning

arXiv:2610.00849 · cs.AI, stat.ML · Submitted 2026-10-01 · Read on arXiv

cs.AI, stat.ML

Submitted: 2026-10-01

Updated: 2026-10-01

Code: https://github.com/pedroroblesduten/GITA

Terminology

• Abstraction — 105× in this paper · explained in 1 episode
• Reinforcement Learning — 24× in this paper · explained in 4 episodes
• Temporal Abstraction — 20× in this paper · explained in 2 episodes
• Ablation — 13× in this paper · explained in 1 episode
• Aggregation — 10× in this paper · explained in 1 episode
• Actor — 7× in this paper · explained in 3 episodes
• In International Conference on Machine Learning — 6× in this paper
• Q-learning — 5× in this paper · explained in 3 episodes
• Generalized Implicit Temporal Abstraction — 4× in this paper
• Adam — 3× in this paper · explained in 2 episodes
• Advantage-Weighted Regression — 3× in this paper
• Benchmark — 3× in this paper · explained in 2 episodes
• Geometric Distribution — 3× in this paper · explained in 2 episodes
• In International Conference on Learning Representations — 3× in this paper
• Ablation Studies — 2× in this paper · explained in 1 episode
• Action Space — 2× in this paper · explained in 1 episode
• Advantage-Progress Correlation — 2× in this paper
• Gaussian Error Linear Unit — 2× in this paper
• Trace — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Action Chunking — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Reward Function — 1× in this paper · explained in 2 episodes

Sources

• Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning
• Layer Normalization
• Gaussian Error Linear Units (GELUs)
• Recursive Value Learning for Long-Horizon Offline Goal-Conditioned RL
• Adaptive Coarse-to-Fine Subgoal Refinement for Long-Horizon Offline Goal-Conditioned Reinforcement Learning
• Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
• Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
• Abstraction for Offline Goal-Conditioned Reinforcement Learning

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