[42] Wenhu Chen, Xueguang Ma, Xinyi Wang, and William W Cohen. Program of thoughts prompting: Disentangling computation from reasoning for numerical reasoning tasks. arXiv preprint arXiv:2211.12588, 2022.
[43] Joshua Brett Tenenbaum. A Bayesian framework for concept learning. PhD thesis, Massachusetts Institute of Technology, 1999.
[44] Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong. Codegen: An open large language model for code with multi-turn program synthesis. arXiv preprint, 2022.
[45] Nils Reimers and Iryna Gurevych. Sentence-bert: Sentence embeddings using siamese bert-networks. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 11 2019.
[46] Diederik P Kingma and Jimmy Ba. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980, 2014.
[47] Alexandru Niculescu-Mizil and Rich Caruana. Predicting good probabilities with supervised learning. In Proceedings of the 22nd international conference on Machine learning, pages 625-632, 2005.
[48] Stephen Muggleton. Inductive logic programming. New generation computing, 8:295-318, 1991.
[49] Andrew Cropper, Sebastijan Dumančić, Richard Evans, and Stephen H Muggleton. Inductive logic programming at 30. Machine Learning, pages 1-26, 2022.
[50] Stanley Kok and Pedro Domingos. Learning the structure of markov logic networks. In Proceedings of the 22nd international conference on Machine learning, pages 441-448, 2005.
[51] Charles Kemp and Terry Regier. Kinship categories across languages reflect general communicative principles. Science, 336(6084):1049-1054, 2012.
[52] Marie Amalric, Liping Wang, Pierre Pica, Santiago Figueira, Mariano Sigman, and Stanislas Dehaene. The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers. PLoS computational biology, 13(1):e1005273, 2017.
[53] Steven T Piantadosi. The computational origin of representation. *Minds and machines*, 31:1-58, 2021.
[54] Lisa Feigenson, Stanislas Dehaene, and Elizabeth Spelke. Core systems of number. Trends in cognitive sciences, 8(7):307-314, 2004.
[55] Steven T Piantadosi, Joshua B Tenenbaum, and Noah D Goodman. The logical primitives of thought: Empirical foundations for compositional cognitive models. Psychological review, 123(4):392, 2016.
[56] John R Anderson and Lael J Schooler. Reflections of the environment in memory. Psychological science, 2(6):396-408, 1991.
[57] Steven Piantadosi. Fleet. https://github.com/piantado/Fleet/, 2023. [Online GitHub repository].
[58] Maryellen C MacDonald. Probabilistic constraints and syntactic ambiguity resolution. Language and cognitive processes, 9(2):157-201, 1994.
[59] Steven T Piantadosi. The computational origin of representation and conceptual change. 2016.
[60] Jeanne Ellis Ormrod. Human learning. Pearson Higher Ed, 2016.
[61] Charles Kemp and Joshua B Tenenbaum. The discovery of structural form. Proceedings of the National Academy of Sciences, 105(31):10687-10692, 2008.
[62] Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, and Jacob Andreas. Leveraging language to learn program abstractions and search heuristics. In International Conference on Machine Learning, 2021.
[63] Taisuke Sato and Yoshitaka Kameya. Prism: a language for symbolic-statistical modeling. In IJCAI, volume 97, pages 1330-1339, 1997.
[64] Matthew Richardson and Pedro Domingos. Markov logic networks. Machine learning, 62:107-136, 2006.
[65] Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, and Luc De Raedt. Deepproblog: Neural probabilistic logic programming. In NIPS, 2018.