Dillon Z. Chen

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I am a PhD student working on theoretical foundations and algorithms for generalised, automated planning. Automated planning is concerned with sequential decision making problems formally specified by structured and symbolic models, and the associated theory and algorithms for solving them. Generalised planning is concerned with synthesising learned knowledge or programs that can extrapolate to and solve unseen tasks exhibiting objects, initial states and goals, and actions not seen in the training set.

So far I have worked on various delicious flavours of planning, including

numeric planning,
multi-objective planning,
stochastic planning,
non-deterministic planning, and
hierarchical planning.

I am also well adversed with machine learning research, with publications in

large language models,
graph neural networks,
foundation models,
graph kernels, and
applications.

For more research, keep reading below. To play the dog gacha, refresh the page (rates and rarities coming soon!).

News

[2025.11]	Paper accepted for an oral presentation at AAAI-26.
[2025.11]	I will be presenting the Learning for Generalised Planning Tutorial at ICAPS-25.
[2025.09]	I am visiting EWRL-25 and the Tübingen AI Center. Thanks Johannes for the invitation!

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Publications

Selected publications are marked with

Conference papers

[C12]	Dillon Z. Chen, Till Hofmann, Toryn Q. Klassen, and Sheila A. McIlraith. Satisficing and Optimal Generalised Planning via Goal Regression. In Proceedings of the 40th AAAI Conference on Artificial Intelligence, 2026. Oral. [ pdf \| code ]
[C11]	Dillon Z. Chen. Weisfeiler-Leman Features for Planning: A 1,000,000 Sample Size Hyperparameter Study. In Proceedings of the 28th European Conference on Artificial Intelligence (ECAI), 2025.
[C10]	Mingyu Hao, Dillon Z. Chen, Felipe Trevizan, and Sylvie Thiébaux. Effective Data Generation and Feature Selection in Learning for Planning. In Proceedings of the 28th European Conference on Artificial Intelligence (ECAI), 2025. Oral.
[C9]	Rebecca Eifler, Nika Beriachvili, Arthur Bit-Monnot, Dillon Z. Chen, Jan Eisenhut, Jörg Hoffmann, Sylvie Thiébaux, and Florent Teichteil-Königsbuch. An Operator-Centric Trustable Decision-Making Tool for Planning Ground Logistic Operations of Beluga Aircraft. In Proceedings of the 28th European Conference on Artificial Intelligence (ECAI), 2025.
[C8]	Dillon Z. Chen and Sylvie Thiébaux. Graph Learning for Numeric Planning. In Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS), 2024. [ pdf \| slides \| poster \| code ]
[C7]	Dillon Z. Chen and Sylvie Thiébaux. Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning. In Proceedings of the 17th International Symposium on Combinatorial Search (SoCS), 2024. Oral. [ pdf \| slides \| poster \| code ]
[C6]	Dillon Z. Chen, Felipe Trevizan, and Sylvie Thiébaux. Return to Tradition: Learning Reliable Heuristics with Classical Machine Learning. In Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS), 2024. Oral. [ pdf \| slides \| poster \| code \| plots ]
[C5]	Dillon Z. Chen, Sylvie Thiébaux, and Felipe Trevizan. Learning Domain-Independent Heuristics for Grounded and Lifted Planning. In Proceedings of the 38th AAAI Conference on Artificial Intelligence, 2024. Oral. [ pdf \| slides \| poster \| code ]
[C4]	Qing Wang, Dillon Z. Chen, Asiri Wijesinghe, Shouheng Li, and Muhammad Farhan. N-WL: A New Hierarchy of Expressivity for Graph Neural Networks. In Proceedings of the 11th International Conference on Learning Representations (ICLR), 2023. [ pdf \| slides \| poster \| code ]
[C3]	Dillon Z. Chen, Felipe Trevizan, and Sylvie Thiébaux. Heuristic Search for Multi-Objective Probabilistic Planning. In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023. Oral. [ pdf \| slides \| poster ]
[C2]	Dillon Z. Chen and Pascal Bercher. The Complexity of Flexible FOND HTN Planning. In Proceedings of the 32nd International Conference on Automated Planning and Scheduling (ICAPS), 2022. Best Undergraduate Student Paper Award. [ pdf \| slides \| poster ]
[C1]	Dillon Z. Chen and Pascal Bercher. Fully Observable Nondeterministic HTN Planning – Formalisation and Complexity Results. In Proceedings of the 31st International Conference on Automated Planning and Scheduling (ICAPS), 2021. Best Undergraduate Student Paper Award. [ pdf \| slides \| poster ]

Workshop papers

[W9]	Dillon Z. Chen. Symmetry-Invariant Novelty Heuristics via Unsupervised Weisfeiler-Leman Features. In Proceedings of the ICAPS 2025 Workshop on Heuristics and Search for Domain-independent Planning (HSDIP), 2025. [ pdf ]
[W8]	Dillon Z. Chen, Johannes Zenn, Tristan Cinquin, and Sheila A. McIlraith. Language Models For Generalised PDDL Planning: Synthesising Sound and Programmatic Policies. In Proceedings of the RLC 2025 Workshop on Programmatic Reinforcement Learning, and 18th European Workshop on Reinforcement Learning (EWRL), 2025. [ pdf \| slides ]
[W7]	Dillon Z. Chen, Till Hofmann, Toryn Q. Klassen, and Sheila A. McIlraith. MOOSE: Satisficing and Optimal Generalised Planning via Goal Regression. In Proceedings of the 1st International Workshop on Trends in Knowledge Representation and Reasoning (TKR), 2025. [ pdf \| slides ]
[W6]	Dillon Z. Chen. STRIPS2DyPDL: A Translator from Automated Planning Problems into Domain-Independent Dynamic Programming Problems. In Proceedings of the 24th Workshop on Constraint Modelling and Reformulation (ModRef), 2025. [ pdf \| slides \| code ]
[W5]	Dillon Z. Chen, Mingyu Hao, Sylvie Thiébaux, and Felipe Trevizan. Graph Learning for Planning: The Story Thus Far and Open Challenges. In Proceedings of the 8th Workshop on Generalization in Planning (GenPlan), 2025. [ pdf \| slides \| poster ]
[W4]	Dillon Z. Chen, Pulkit Verma, Siddharth Srivastava, Michael Katz, and Sylvie Thiébaux. AI Planning: A Primer and Survey (Preliminary Report). In Proceedings of the 8th Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL), 2025. [ pdf \| slides ]
[W3]	Dillon Z. Chen, Sylvie Thiébaux, and Felipe Trevizan. GOOSE: Learning Domain-Independent Heuristics. In Proceedings of the 7th Workshop on Generalization in Planning (GenPlan), 2023. «Subsumed by [C5]». [ pdf \| slides \| poster ]
[W2]	Dillon Z. Chen, Felipe Trevizan, and Sylvie Thiébaux. Graph Neural Networks and Graph Kernels For Learning Heuristics: Is there a difference?. In Proceedings of the 7th Workshop on Generalization in Planning (GenPlan), 2023. «Subsumed by [C6]». [ pdf \| poster ]
[W1]	Dillon Z. Chen and Pascal Bercher. The Complexity of Flexible FOND HTN Planning. In Proceedings of the 4th ICAPS Workshop on Hierarchical Planning (HPlan), 2021. «Subsumed by [C2]». [ pdf ]

Theses

[T1]	Dillon Z. Chen. GOOSE: Learning Heuristics and Parallelising Search for Grounded and Lifted Planning. Bachelor thesis, The Australian National University, 2023. [ pdf ]

Miscellaneous Links

Congrats on scrolling down this far.

[2025.09]	Most excited to visit the Machine Reasoning Lab at Linköping University. Thanks Jendrik for the invitation!
[2025.07]	3 papers accepted to ECAI-25 and workshop papers accepted to TKR@IJCAI-25, ModRef@CP-25, PRL@RLC-25, and EWRL-25.
[2025.02]	Most excited to research intern at Vector Institute. Thanks Sheila for the invitation!
[2025.01]	140kg bench press achieved.
[2024.12]	Papers accepted to GenPlan and PRL workshops at AAAI-25.
[2024.10]	One year milestone!
[2024.09]	Paper accepted to NeurIPS-24.
[2024.09]	I am giving a talk at the Aachen RLeap Symposium. Thanks Hector for the invitation!
[2024.06]	WLPlan, a library implementating the WL Features for PDDL planning described in our ICPAS-24 paper, is now available as an alpha release.
[2024.06]	I am visiting ICAPS-24 in Banff and SOCS-24 in Kananaskis.
[2024.05]	Most excited to visit the RLeap Lab at RWTH Aachen. Thanks Hector for hosting!
[2024.04]	Most excited to visit CVUT in Prague. Thanks Rostislav and Gustav for hosting!
[2024.02]	I am visiting AAAI-24 in Vancouver.
[2024.02]	I am giving a talk at the ANU AI ML Friends seminar.
[2023.12]	I am visiting NeurIPS 2023 in New Orleans.
[2023.10]	I started my PhD.