mlsanityData to 14 Oct 2026

Learning Curriculum Policies for Reinforcement Learning

arXiv 1812.00285 ↗First posted 1 Dec 2018cs.LG cs.AI stat.MLcited by 35

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Abstract (arXiv)

Curriculum learning in reinforcement learning is a training methodology that seeks to speed up learning of a difficult target task, by first training on a series of simpler tasks and transferring the knowledge acquired to the target task. Automatically choosing a sequence of such tasks (i.e. a curriculum) is an open problem that has been the subject of much recent work in this area. In this paper, we build upon a recent method for curriculum design, which formulates the curriculum sequencing problem as a Markov Decision Process. We extend this model to handle multiple transfer learning algorithms, and show for the first time that a curriculum policy over this MDP can be learned from experience. We explore various representations that make this possible, and evaluate our approach by learning curriculum policies for multiple agents in two different domains. The results show that our method produces curricula that can train agents to perform on a target task as fast or faster than existing methods.

Key facts. Cited by 35 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Dec 2018.

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Citing papers per year: 2020: 1; 2021: 7; 2022: 9; 2023: 6; 2024: 3; 2025: 4; 2026: 5.

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  1. 2021Curriculum Learning: A Surveycited by 259
  2. 2021Autonomous Reinforcement Learning via Subgoal Curriculacited by 33
  3. 2022Environment Generation for Zero-Shot Compositional Reinforcement Learningcited by 32
  4. 2021A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learningcited by 22
  5. 2023Proximal Curriculum for Reinforcement Learning Agentscited by 20
  6. 2021RLOps: Development Life-cycle of Reinforcement Learning Aided Open RANcited by 15
  7. 2022Robust Reinforcement Learning via Genetic Curriculumcited by 10
  8. 2023Cross-Episodic Curriculum for Transformer Agentscited by 10
  9. 2021Curriculum Design for Teaching via Demonstrations: Theory and Applicationscited by 9
  10. 2023Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skillscited by 9
  11. 2022Relational Abstractions for Generalized Reinforcement Learning on Symbolic Problemscited by 7
  12. 2024Proximal Curriculum with Task Correlations for Deep Reinforcement Learningcited by 7
23 more
  1. 2022Learning to Transfer Role Assignment Across Team Sizescited by 5
  2. 2023Towards Skilled Population Curriculum for Multi-Agent Reinforcement Learningcited by 4
  3. 2021Investigating Value of Curriculum Reinforcement Learning in Autonomous Driving Under Diverse Road and Weather Conditionscited by 3
  4. 2021Learning Multi-Objective Curricula for Robotic Policy Learningcited by 3
  5. 2022Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planningcited by 3
  6. 2025Heterogeneous Adversarial Play in Interactive Environmentscited by 3
  7. 2026ReRec: Reasoning-Augmented LLM-based Recommendation Assistant via Reinforcement Fine-tuningcited by 3
  8. 2022Teacher-student curriculum learning for reinforcement learningcited by 2
  9. 2023A Comprehensive Study of Privacy Risks in Curriculum Learningcited by 2
  10. 2024Mitigating the Stability-Plasticity Dilemma in Adaptive Train Scheduling with Curriculum-Driven Continual DQN Expansioncited by 2
  11. 2025Probabilistic Curriculum Learning for Goal-Based Reinforcement Learningcited by 2
  12. 2025AURA: Autonomous Upskilling with Retrieval-Augmented Agentscited by 2
  13. 2022Reinforcement Teachingcited by 1
  14. 2022Multi-Phase Multi-Objective Dexterous Manipulation with Adaptive Hierarchical Curriculumcited by 1
  15. 2023Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robotcited by 1
  16. 2024Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approachcited by 1
  17. 2025ForceGrip: Reference-Free Curriculum Learning for Realistic Grip Force Control in VR Hand Manipulationcited by 1
  18. 2020Interaction-limited Inverse Reinforcement Learningcited by 0
  19. 2022Autonomous Open-Ended Learning of Tasks with Non-Stationary Interdependenciescited by 0
  20. 2026Decoupling Task and Behavior: A Two-Stage Reward Curriculum in Reinforcement Learning for Roboticscited by 0
  21. 2026Balancing the Reasoning Load: Difficulty-Differentiated Policy Optimization with Length Redistribution for Efficient and Robust Reinforcement Learningcited by 0
  22. 2026A Single Diffusion-Policy Controller for Multi-Task Block Pushing with Zero-Shot Sim-to-Real Transfercited by 0
  23. 2026Anticipating the Consequences of Curriculum Decisions with Large Language Modelscited by 0