🧑‍🔬 Leslie Pack Kaelbling

🏛️ Affiliations

🎓Massachusetts Institute of TechnologyCambridge · United States2000–2026 · 199 paperscurrent🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge · United States2002–2026 · 116 paperscurrent🎓Brown UniversityProvidence · United States1993–2019 · 35 papers🎓Stanford UniversityStanford · United States1986–1991 · 5 papers🔬SRI InternationalMenlo Park · United States1986–1988 · 5 papers🎓Duke UniversityDurham · United States1998–2018 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Generalized Planning in PDDL Domains with Pretrained Large Language Models (2023 · 112 citations)
   The paper asks whether a pretrained LLM can be a generalized planner rather than a per-task planner. Given a PDDL domain and a few training tasks, the model should produce a program that quickly outputs valid plans for new, usually much larger tasks in that domain. GPT-4 receives the domain and two abbreviated…
2. Learning Interactive Real-World Simulators (2023 · 54 citations)
   The paper asks whether a generative model can serve as an interactive simulator of the real world, producing the visual result of an action applied to a scene.
3. Scaling Exponents Across Parameterizations and Optimizers (2024 · 15 citations)
   Scaling a Transformer from small to large width requires choosing how the initialization, parameter multipliers and learning rates change with width.

All works

19 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. Reinforcement Learning: A Survey ↗Journal of Artificial Intelligence Research · no summary yetLeslie Pack Kaelbling, Michael L. Littman, Andrew Moore1996 · 9,005 citations
2. Learning Symbolic Models of Stochastic Domains ↗Journal of Artificial Intelligence Research · no summary yetHanna Pasula, Luke Zettlemoyer, Leslie Pack Kaelbling2007 · 187 citations
3. Generalized Planning in PDDL Domains with Pretrained Large Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceTom Silver, Soham Dan, Kavitha Srinivas, et al.2023 · 112 citations
4. Learning planning rules in noisy stochastic worlds ↗no summary yetLuke Zettlemoyer, Hanna Pasula, Leslie Pack Kaelbling2005 · 65 citations
5. Learning Interactive Real-World SimulatorsarXiv:2310.06114Sherry Yang, Yilun Du, Kamyar Ghasemipour, et al.2023 · 54 citations
6. Learning probabilistic relational planning rules ↗no summary yetHanna Pasula, Luke Zettlemoyer, Leslie Pack Kaelbling2003 · 52 citations
7. Multi-Agent Filtering with Infinitely Nested Beliefs ↗no summary yetLuke Zettlemoyer, Brian Milch, Leslie Pack Kaelbling2008 · 20 citations
8. Scaling Exponents Across Parameterizations and OptimizersarXiv:2407.05872Katie Everett, Lechao Xiao, Mitchell Wortsman, et al.2024 · 15 citations
9. Learning Probabilistic Relational Dynamics for Multiple Tasks ↗arXiv (Cornell University) · no summary yetAshwin Deshpande et al.2012 · 11 citations
10. Logical Particle Filtering ↗DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · no summary yetLuke Zettlemoyer, Hanna Pasula, Leslie Pack Kaelbling2008 · 10 citations
11. Learning and Planning with Probabilistic Relational Rules ↗no summary yetHanna Pasula et al.2004 · 5 citations
12. Reasoning about Large Populations with Lifted Probabilistic Inference ↗no summary yetKristian Kersting et al.2007 · 4 citations
13. Learning Planning Rules in Stochastic Worlds ↗National Conference on Artificial Intelligence · no summary yetLuke Zettlemoyer, Hanna Pasula, Leslie Pack Kaelbling2005 · 1 citation
14. Learning Probabilistic Planning Rules ↗no summary yetHanna Pasula, Luke Zettlemoyer, Leslie Pack Kaelbling2014
15. Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (2008) Lifted Probabilistic Inference with Counting Formulas ↗no summary yetBrian Milch et al.2013
16. Kaelbling. Learning symbolic models of stochastic domains ↗no summary yetHanna Pasula, Luke Zettlemoyer, Leslie Pack Kaelbling2008
17. Kaelbling. Learning planning rules in noisy stochastic worlds ↗no summary yetLuke Zettlemoyer, Hanna Pasula, Leslie Pack Kaelbling2005
18. Reaching for Dexterous Manipulation MIT EECS Area Exam ↗no summary yetExam Committee et al.2003
19. Shortest Paths in a Dynamic Uncertain Domain ↗no summary yetDavid M. Blei, Leslie Pack Kaelbling1999

🤝 Co-authors here

12 of 15 co-authors with a page, the most papers together first.

• Alexander A. Alemi
• Dale Schuurmans
• Izzeddin Gur
• Jaehoon Lee
• Jascha Sohl-Dickstein
• Jeffrey Pennington
• Joshua B. Tenenbaum
• Kavitha Srinivas
• Michael Katz
• Mitchell Wortsman
• Peter J. Liu
• Pieter Abbeel

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Journal of Artificial Intelligence Research ×2
• Proceedings of the AAAI Conference on Artificial Intelligence: Proceedings of the AAAI Conference on Artificial Intelligence 2023
• DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
• National Conference on Artificial Intelligence

🔗 Cited by

Papers of our library cite their works 185 times (of the 149,439 papers whose bibliographies we read); 40 citing papers with a page here →.

Updated 3 November 2026

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