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Neurosymbolic Programming

A key theme in our research is the use of neurosymbolic programs, i.e., models constructed through the composition of neural networks and traditional symbolic code. The neural modules in such a program facilitate efficient learning, while the symbolic components allow the program to use human domain knowledge and also be human-comprehensible. Our research studies a wide variety of challenges in neurosymbolic programming, including the design of language abstractions that allow neural and symbolic modules to interoperate smoothly, methods for analyzing the safety and performance of neurosymbolic programs, and algorithms for learning the structure and parameters of neurosymbolic programs from data.


Selected Publications

Anderson, Greg; Verma, Abhinav; Dillig, Isil; Chaudhuri, Swarat

Neurosymbolic Reinforcement Learning with Formally Verified Exploration Inproceedings

In: Larochelle, Hugo; Ranzato, Marc'Aurelio; Hadsell, Raia; Balcan, Maria-Florina; Lin, Hsuan-Tien (Ed.): Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.

Links | BibTeX

Shah, Ameesh; Zhan, Eric; Sun, Jennifer J.; Verma, Abhinav; Yue, Yisong; Chaudhuri, Swarat

Learning Differentiable Programs with Admissible Neural Heuristics Inproceedings

In: Larochelle, Hugo; Ranzato, Marc'Aurelio; Hadsell, Raia; Balcan, Maria-Florina; Lin, Hsuan-Tien (Ed.): Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.

Links | BibTeX

Verma, Abhinav; Le, Hoang Minh; Yue, Yisong; Chaudhuri, Swarat

Imitation-Projected Programmatic Reinforcement Learning Inproceedings

In: Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14 December 2019, Vancouver, BC, Canada, pp. 15726–15737, 2019.

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Cheng, Richard; Verma, Abhinav; Orosz, Gábor; Chaudhuri, Swarat; Yue, Yisong; Burdick, Joel

Control Regularization for Reduced Variance Reinforcement Learning Inproceedings

In: Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, pp. 1141–1150, 2019.

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Kevin Ellis Swarat Chaudhuri, Oleksandr Polozov; Yue, Yisong

Neurosymbolic Programming. Foundations and Trends in Programming Languages. Book

2018.

BibTeX

Valkov, Lazar; Chaudhari, Dipak; Srivastava, Akash; Sutton, Charles; Chaudhuri, Swarat

HOUDINI: Lifelong Learning as Program Synthesis Inproceedings

In: Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, 3-8 December 2018, Montréal, Canada, pp. 8701–8712, 2018.

Links | BibTeX