Recursive Value Learning for Long-Horizon Offline Goal-Conditioned RL

arXiv:2609.02237 · cs.LG, cs.RO · Submitted 2026-09-02 · Read on arXiv

cs.LG, cs.RO

Submitted: 2026-09-02

Updated: 2026-09-02

Terminology

• Reinforcement Learning — 18× in this paper · explained in 4 episodes
• Ablation — 10× in this paper · explained in 1 episode
• Benchmark — 9× in this paper · explained in 2 episodes
• Grounding — 7× in this paper · explained in 3 episodes
• In International Conference on Learning Representations — 7× in this paper
• International Conference on Machine Learning — 7× in this paper
• Monte Carlo — 7× in this paper
• Actor — 5× in this paper · explained in 3 episodes
• Temporal Difference — 5× in this paper
• Ablation Studies — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• In Conference on Robot Learning — 3× in this paper
• Stochastic Dynamics — 3× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 2× in this paper · explained in 2 episodes
• Q-learning — 2× in this paper · explained in 3 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Action Space — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Divide-and-Conquer Reinforcement Learning — 1× in this paper
• Fidelity — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes

Sources

• Floyd-Warshall Reinforcement Learning: Learning from Past Experiences to Reach New Goals
• Regularized Behavior Value Estimation
• IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies
• Gaussian Error Linear Units (GELUs)
• Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning

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