Dillon Ze Chen 


        E: dillon dot chen 1 at gmail dot com
        T: +33 05 61 33 63 48
        W: https://dillonzchen.github.io

I am a PhD student in automated planning and machine learning supervised by Sylvie Thiébaux in the RIS team.

For research, keep reading below.

Links 

[dblp] [Google Scholar] [🧦 GitHub] [CV]
[ICAPS Visualisations]
[Paper Checklist]

News

[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!
[expand]

Research Interests

I work in the union of machine learning and sequential decision making, with a particular focus in the field of automated planning. My starry-eyed thesis goal is to scale up planning technology to real-world scenarios involving humongous numbers of objects.

So far I have worked on various delicious flavours of planning, including numeric, multi-objective, stochastic, non-deterministic, and hierarchical planning.

I can also keep up to date with machine learning research, with publications in graph neural networks, foundation models, graph kernels, and applications.

Publications

ICAPS, AAAI, NeurIPS and ICLR are A* conferences.

Conference papers

[C8] Dillon Ze Chen and Sylvie Thiébaux. Graph Learning for Numeric Planning. In 38th Conference on Neural Information Processing Systems (NeurIPS), 2024. 
[ pdf | poster | slides | code ]
[C7] Dillon Ze Chen and Sylvie Thiébaux. Novelty Heuristics, Multi-Queue Search, and Portfolios for Numeric Planning. In 17th International Symposium on Combinatorial Search (SoCS), 2024. 
[ pdf | poster | slides | code ]
[C6] Dillon Ze Chen, Felipe Trevizan, and Sylvie Thiébaux. Return to Tradition: Learning Reliable Heuristics with Classical Machine Learning. In 34th International Conference on Automated Planning and Scheduling (ICAPS), 2024. 
[ pdf | poster | slides | code | plots ]
[C5] Dillon Ze Chen, Sylvie Thiébaux, and Felipe Trevizan. Learning Domain-Independent Heuristics for Grounded and Lifted Planning. In 38th AAAI Conference on Artificial Intelligence, 2024. 
[ pdf | poster | slides | code ]
[C4] Qing Wang, Dillon Ze Chen, Asiri Wijesinghe, Shouheng Li, and Muhammad Farhan. N-WL: A New Hierarchy of Expressivity for Graph Neural Networks. In 11th International Conference on Learning Representations (ICLR), 2023. 
[ pdf | poster | slides | code ]
[C3] Dillon Ze Chen, Felipe Trevizan, and Sylvie Thiébaux. Heuristic Search for Multi-Objective Probabilistic Planning. In 37th AAAI Conference on Artificial Intelligence, 2023. 
[ pdf | poster | slides | code ]
[C2] Dillon Ze Chen and Pascal Bercher. The Complexity of Flexible FOND HTN Planning. In 32nd International Conference on Automated Planning and Scheduling (ICAPS), 2022. Best Undergraduate Student Paper Award. 
[ pdf | poster | slides ]
[C1] Dillon Ze Chen and Pascal Bercher. Fully Observable Nondeterministic HTN Planning – Formalisation and Complexity Results. In 31st International Conference on Automated Planning and Scheduling (ICAPS), 2021. Best Undergraduate Student Paper Award. 
[ pdf | poster | slides ]

Workshop papers

[W3] Dillon Ze Chen, Sylvie Thiébaux, and Felipe Trevizan. GOOSE: Learning Domain-Independent Heuristics. In 7th Workshop on Generalization in Planning (GenPlan), 2023. «Subsumed by [C5]». 
[ pdf | poster | slides ]
[W2] Dillon Ze Chen, Felipe Trevizan, and Sylvie Thiébaux. Graph Neural Networks and Graph Kernels For Learning Heuristics: Is there a difference?. In 7th Workshop on Generalization in Planning (GenPlan), 2023. «Subsumed by [C6]». 
[ pdf | poster ]
[W1] Dillon Ze Chen and Pascal Bercher. The Complexity of Flexible FOND HTN Planning. In 4th ICAPS Workshop on Hierarchical Planning (HPlan), 2021. «Subsumed by [C2]». 
[ pdf ]

Reviewing

I have reviewed for the following conferences and workshops, listed in alphabetical order.

Conferences

Workshops

Clocks

Time zone map


        

        
        

        

        

        

        

        

        

        

        

        
        
        

        
            
        

        

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