mlsanityData to 7 Oct 2026

Goal-Conditioned Decision Transformer for Multi-Goal Offline Reinforcement Learning

arXiv 2410.06347 ↗First posted 8 Oct 2024cs.RO cs.AIcited by 2

On the map: Offline RL and imitation learning from data → Decision transformers and sequence modeling

Abstract (arXiv)

Reinforcement learning (RL) in robotics faces significant hurdles regarding sample efficiency and generalization across varying goals. While Offline RL mitigates the need for costly online interactions, its integration with goal-conditioned policies and transformer-based architectures remains underexplored. We introduce a Goal-Conditioned Decision Transformer adapted for offline multi-goal robotics. By explicitly incorporating goal states into the sequence modeling framework, our approach efficiently solves varying tasks using only pre-collected data. We validate this method on a newly released offline dataset for the Franka Emika Panda platform. Experimental results demonstrate that our approach outperforms state-of-the-art online baselines in complex tasks and maintains robustness in sparse-reward settings, even with limited expert demonstrations.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Decision transformers and sequence modeling, one of 13 directions in Offline RL and imitation learning from data. Builds on 9 of its 12 references that are in the map. First posted on arXiv 8 Oct 2024.

Builds on

9 of 12 references.

Closest ancestors · 1

Same direction, newest first

  1. 2021Decision Transformer: Reinforcement Learning via Sequence Modeling2 Jun

Other references · 8

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,635
  3. 2013Playing Atari with Deep Reinforcement Learningcited by 3,211
  4. 2017Hindsight Experience Replaycited by 1,096
  5. 2018Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Researchcited by 256
  6. 2020Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Criticscited by 154
  7. 2021Accelerating Robotic Reinforcement Learning via Parameterized Action Primitivescited by 63
  8. 2021panda-gym: Open-source goal-conditioned environments for robotic learningcited by 56

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Cited by year

Citing papers per year: 2025: 2.

2 papers.

  1. 2025GRoQ-LoCO: Generalist and Robot-agnostic Quadruped Locomotion Control using Offline Datasetscited by 1
  2. 2025HySafe-AI: Hybrid Safety Architectural Analysis Framework for AI Systems: A Case Studycited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023Multi-Objective Decision Transformers for Offline Reinforcement Learning
  2. 2025Should We Ever Prefer Decision Transformer for Offline Reinforcement Learning?
  3. 2022Hierarchical Planning Through Goal-Conditioned Offline Reinforcement Learning
  4. 2023Goal-conditioned Offline Reinforcement Learning through State Space Partitioning
  5. 2022Planning to Practice: Efficient Online Fine-Tuning by Composing Goals in Latent Space
  6. 2022Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL
  7. 2021Offline Reinforcement Learning as One Big Sequence Modeling Problem
  8. 2024Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?