mlsanityData to 14 Oct 2026

Habitizing Diffusion Planning for Efficient and Effective Decision Making

arXiv 2502.06401 ↗First posted 10 Feb 2025cs.LGcited by 7

On the map: Diffusion models → Diffusion and flow policies for robotics

also in 1 more
Abstract (arXiv)

Diffusion models have shown great promise in decision-making, also known as diffusion planning. However, the slow inference speeds limit their potential for broader real-world applications. Here, we introduce Habi, a general framework that transforms powerful but slow diffusion planning models into fast decision-making models, which mimics the cognitive process in the brain that costly goal-directed behavior gradually transitions to efficient habitual behavior with repetitive practice. Even using a laptop CPU, the habitized model can achieve an average 800+ Hz decision-making frequency (faster than previous diffusion planners by orders of magnitude) on standard offline reinforcement learning benchmarks D4RL, while maintaining comparable or even higher performance compared to its corresponding diffusion planner. Our work proposes a fresh perspective of leveraging powerful diffusion models for real-world decision-making tasks. We also provide robust evaluations and analysis, offering insights from both biological and engineering perspectives for efficient and effective decision-making.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 40 of its 65 references that are in the map. First posted on arXiv 10 Feb 2025.

Builds on

40 of 65 references.

Closest ancestors · 12

Same direction, newest first

  1. 2024Diffusion Policy Policy Optimization1 Sep
  2. 2024Diffusion Policies creating a Trust Region for Offline Reinforcement Learning30 May
  3. 2024Diffusion Actor-Critic with Entropy Regulator24 May
  4. 20243D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations6 Mar
  5. 2023Learning a Diffusion Model Policy from Rewards via Q-Score Matching18 Dec
  6. 2023Score Regularized Policy Optimization through Diffusion Behavior11 Oct
  7. 2023Policy Representation via Diffusion Probability Model for Reinforcement Learning22 May
  8. 2023IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies20 Apr
  9. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusion7 Mar
  10. 2023AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners3 Feb
  11. 2022Is Conditional Generative Modeling all you need for Decision-Making?28 Nov
  12. 2022Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning12 Aug

Other references · 28

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2020Denoising Diffusion Implicit Modelscited by 9,781
  3. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
  4. 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,979
  5. 2020Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problemscited by 1,920
  6. 2020Conservative Q-Learning for Offline Reinforcement Learningcited by 1,809
  7. 2021Offline Reinforcement Learning with Implicit Q-Learningcited by 1,293
  8. 2018Learning Latent Dynamics for Planning from Pixelscited by 1,264
  9. 2023Mastering Diverse Domains through World Modelscited by 1,253
  10. 2018Off-Policy Deep Reinforcement Learning without Explorationcited by 1,241
  11. 2018Soft Actor-Critic Algorithms and Applicationscited by 1,240
  12. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,219
16 more
  1. 2022Planning with Diffusion for Flexible Behavior Synthesiscited by 1,061
  2. 2016Deep Variational Information Bottleneckcited by 930
  3. 2018Recurrent World Models Facilitate Policy Evolutioncited by 785
  4. 2021Offline Reinforcement Learning as One Big Sequence Modeling Problemcited by 644
  5. 2023Learning Universal Policies via Text-Guided Video Generationcited by 522
  6. 2018Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Reviewcited by 482
  7. 2015A Recurrent Latent Variable Model for Sequential Datacited by 362
  8. 2021Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemblecited by 302
  9. 2022Offline Reinforcement Learning via High-Fidelity Generative Behavior Modelingcited by 182
  10. 2022RORL: Robust Offline Reinforcement Learning via Conservative Smoothingcited by 84
  11. 2024Bridging State and History Representations: Understanding Self-Predictive RLcited by 54
  12. 2019Variational Recurrent Models for Solving Partially Observable Control Taskscited by 47
  13. 2024DiffuserLite: Towards Real-time Diffusion Planningcited by 42
  14. 2024CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Makingcited by 39
  15. 2018VIREL: A Variational Inference Framework for Reinforcement Learningcited by 22
  16. 2023Habits and goals in synergy: a variational Bayesian framework for behaviorcited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 4.

7 papers.

  1. 2025One-Step Flow Q-Learning: Addressing the Diffusion Policy Bottleneck in Offline Reinforcement Learningcited by 11
  2. 2025SAD-Flower: Flow Matching for Safe, Admissible, and Dynamically Consistent Planningcited by 3
  3. 2026Implicit Maximum Likelihood Estimation for Real-time Generative Model Predictive Controlcited by 3
  4. 2026Fast and Highly Expressive Policy Learning for Offline Reinforcement Learning via Bootstrapped Flow Q-Learningcited by 2
  5. 2025PoseDiff: A Unified Diffusion Model Bridging Robot Pose Estimation and Video-to-Action Controlcited by 0
  6. 2026State-Action Inpainting Diffuser for Continuous Control with Delaycited by 0
  7. 2026Compositional Average Velocity Modeling for Efficient Diffusion Offline Reinforcement Learningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025What Makes a Good Diffusion Planner for Decision Making?
  2. 2025Prior-Guided Diffusion Planning for Offline Reinforcement Learning
  3. 2026Diffusion Modulation via Environment Mechanism Modeling for Planning
  4. 2025Accelerating Diffusion Planners in Offline RL via Reward-Aware Consistency Trajectory Distillation
  5. 2024Diffusion Models as Optimizers for Efficient Planning in Offline RL
  6. 2026Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making
  7. 2024Simple Hierarchical Planning with Diffusion
  8. 2025Diffusion Models for Reinforcement Learning: Foundations, Taxonomy, and Development