Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning
B. Yalcinkaya*, N. Lauffer*, M. Vazquez-Chanlatte*, S. Seshia. NeurIPS 2024.
Publications
Learning Task Decompositions for Multi‑agent Teams
T. Chen*, N. Pitta*, A. Shah*, N. Lauffer*, S. Seshia. RSS Spec. 2024.
Welfare Diplomacy: Benchmarking Language Model Cooperation
G. Mukobi, H. Erlebach, N. Lauffer, L. Hammond, A. Chan, J. Clifton. arXiv 2024.
Automata Conditioned Reinforcement Learning with Experience Replay
N. Lauffer*, B. Yalcinkaya*, M. Vazquez-Chanlatte, S. Seshia. NeurIPS 2024.
Who Needs to Know? Minimal Knowledge for Optimal Coordination
N. Lauffer, A. Shah, M. Carroll, M. Dennis, and S. Russell. ICML 2023.
No‑regret Learning in Dynamic Stackelberg Games
N. Lauffer, M. Ghasemi, A. Hashemi, Y. Savas, and U. Topcu. arXiv preprint 2022.
Learning Deterministic Finite Automata Decompositions from Examples and Demonstrations
N. Lauffer*, B. Yalcinkaya*, M. Vazquez-Chanlatte, A Shah, and S. Seshia. FMCAD 2022.
Multiscale Heterogeneous Optimal Lockdown Control for COVID-19 Using Geographic Information
C. Neary, M. Cubuktepe, N. Lauffer, X. Jin, A. Phillips, Z. Xu, D. Tong, and U. Topcu. Scientific Reports 2022.
Reachability Games for Optimal Multi-agent Scheduling of Tasks with Variable Durations
Human‑understandable explanations of infeasibility for resource‑constrained scheduling problems
Expedited Learning in MDPs with Side Information
M. Ornik, J. Fu, N. Lauffer, K. W. Perera, M. Alshiekh, M. Ono, and U. Topcu. CDC 2018.
Affine multiplexing networks: System analysis, learning, and computation
I. Papusha, U. Topcu, S. Car, N. Lauffer. arXiv preprint 2018.
*equal authorship
More information is available on my Google Scholar profile.