I'm a PhD student in the Robotics and InteractionS (RIS) team at LAAS-CNRS, under the supervision of Sylvie Thiébaux and Arthur Bit-Monnot. I received the EDMITT Doctoral Fellowship.
Previously, I did my undergraduate at the Australian National University. I received the University Medal for work done during my honours year in computer science, and the Hanna Neumann Prize for Mathematics for my coursework results. I was fortunate enough to work with Pascal Bercher, Qing Wang, Felipe Trevizan and Sylvie Thiébaux.
For research, keep reading below. For esoteric pages, click here (last updated 2022). To play the dog gacha, refresh the page (rates and rarities coming soon!).
I am interested in the intersection of the fields of planning and learning.
Planning is focused on long horizon reasoning and complex problem solving with guarantees. However, planning models suffer from computationally complexity. The tradeoff with planning is between expressivity and scalability: we want planning models which are expressive enough to model practical, real life problems, but are also solvable with reasonable computational resources to be actually used.
Learning is focused on pattern matching and data compression. However, learning models generally do not have guarantees with their outputs. The tradeoff with learning is between expressivity and generalisability: we want learning models which are expressive enough to capture certain patterns, but are also able to generalise to unseen outputs.
| [1] | 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 ] |
| [2] | 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 ] |
| [3] | 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 ] |
| [4] | 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 ] |
| [1] | 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. |
| [2] | Dillon Ze Chen, Sylvie Thiébaux, and Felipe Trevizan. GOOSE: Learning Domain-Independent Heuristics. In 7th Workshop on Generalization in Planning (GenPlan), 2023. |
| [3] | Dillon Ze Chen and Pascal Bercher. The Complexity of Flexible FOND HTN Planning. In 4th ICAPS Workshop on Hierarchical Planning (HPlan), 2021. «Subsumed by [Chen and Bercher, ICAPS-22]». [ pdf ] |