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Generalized Planning With Deep Reinforcement Learning

arXiv 2005.02305 ↗First posted 5 May 2020cs.AI cs.LGcited by 35

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Abstract (arXiv)

A hallmark of intelligence is the ability to deduce general principles from examples, which are correct beyond the range of those observed. Generalized Planning deals with finding such principles for a class of planning problems, so that principles discovered using small instances of a domain can be used to solve much larger instances of the same domain. In this work we study the use of Deep Reinforcement Learning and Graph Neural Networks to learn such generalized policies and demonstrate that they can generalize to instances that are orders of magnitude larger than those they were trained on.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 May 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 7; 2023: 6; 2024: 8; 2025: 7; 2026: 3.

35 papers.

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  1. 2023Generalized Planning in PDDL Domains with Pretrained Large Language Modelscited by 139
  2. 2022TASKOGRAPHY: Evaluating robot task planning over large 3D scene graphscited by 59
  3. 2021Learning Neuro-Symbolic Relational Transition Models for Bilevel Planningcited by 43
  4. 2022Learning Generalized Policies Without Supervision Using GNNscited by 22
  5. 2021Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generatorscited by 21
  6. 2023Explore to Generalize in Zero-Shot RLcited by 20
  7. 2024Return to Tradition: Learning Reliable Heuristics with Classical Machine Learningcited by 19
  8. 2021A Research Agenda for AI Planning in the Field of Flexible Production Systemscited by 8
  9. 2022PG3: Policy-Guided Planning for Generalized Policy Generationcited by 8
  10. 2021Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stabilitycited by 7
  11. 2024Symmetries and Expressive Requirements for Learning General Policiescited by 7
  12. 2023General Policies, Subgoal Structure, and Planning Widthcited by 6
23 more
  1. 2024Unlocking Large Language Model's Planning Capabilities with Maximum Diversity Fine-tuningcited by 6
  2. 2023On Using Admissible Bounds for Learning Forward Search Heuristicscited by 5
  3. 2023LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient Queryingcited by 5
  4. 2022Hierarchical Decomposition and Analysis for Generalized Planningcited by 4
  5. 2023Scale-Adaptive Balancing of Exploration and Exploitation in Classical Planningcited by 4
  6. 2022Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planningcited by 3
  7. 2022Understanding Sample Generation Strategies for Learning Heuristic Functions in Classical Planningcited by 3
  8. 2024Graph Neural Network Based Action Ranking for Planningcited by 3
  9. 2025Per-Domain Generalizing Policies: On Validation Instances and Scaling Behaviorcited by 3
  10. 2025Learning General Policies with Policy Gradient Methodscited by 3
  11. 2024On Policy Reuse: An Expressive Language for Representing and Executing General Policies that Call Other Policiescited by 1
  12. 2024Learning Generalized Policies for Fully Observable Non-Deterministic Planning Domainscited by 1
  13. 2024Learning to Ground Existentially Quantified Goalscited by 1
  14. 2022Scaling up ML-based Black-box Planning with Partial STRIPS Modelscited by 0
  15. 2024Meta-operators for Enabling Parallel Planning Using Deep Reinforcement Learningcited by 0
  16. 2025Scaling Up without Fading Out: Goal-Aware Sparse GNN for RL-based Generalized Planningcited by 0
  17. 2025Integrating Symbolic RL Planning into a BDI-based Autonomous UAV Framework: System Integration and SIL Validationcited by 0
  18. 2025LOOP: A Plug-and-Play Neuro-Symbolic Framework for Enhancing Planning in Autonomous Systemscited by 0
  19. 2025Learning General Policies From Examplescited by 0
  20. 2025GammaZero: Learning To Guide POMDP Belief Space Search With Graph Representationscited by 0
  21. 2026On Sample-Efficient Generalized Planning via Learned Transition Modelscited by 0
  22. 2026Efficient Lookahead Encoding and Abstracted Width for Learning General Policies in Classical Planningcited by 0
  23. 2026Learning to Search and Searching to Learn for Generalization in Planningcited by 0