ABLkit: a Python toolkit for abductive learning

Yu-Xuan HUANG; Wen-Chao HU; En-Hao GAO; Yuan JIANG

doi:10.1007/s11704-024-40085-7

Front. Comput. Sci. ›› 2024, Vol. 18 ›› Issue (6) : 186354 DOI: 10.1007/s11704-024-40085-7

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ABLkit: a Python toolkit for abductive learning

Yu-Xuan HUANG ¹^,²
, Wen-Chao HU ¹^,²
, En-Hao GAO ¹^,²
, Yuan JIANG ¹^,²^,^†

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Yu-Xuan HUANG, Wen-Chao HU, En-Hao GAO, Yuan JIANG. ABLkit: a Python toolkit for abductive learning. Front. Comput. Sci., 2024, 18(6): 186354 DOI:10.1007/s11704-024-40085-7

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References

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[1]	Zhou Z H . Abductive learning: towards bridging machine learning and logical reasoning. Science China Information Sciences, 2019, 62( 7): 76101

[2]	Zhou Z H, Huang Y X. Abductive learning. In: Hitzler P, Sarker M K, eds. Neuro-Symbolic Artificial Intelligence: The State of the Art. Amsterdam: IOS Press, 2022, 353−369

[3]	Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D, Brucher M, Perrot M, Duchesnay É . Scikit-learn: machine learning in python. Journal of Machine Learning Research, 2011, 12( 85): 2825–2830

[4]

Paszke A, Gross S, Massa F, Lerer A, Bradbury J, Chanan G, Killeen T, Lin Z, Gimelshein N, Antiga L, Desmaison A, Köpf A, Yang E, DeVito Z, Raison M, Tejani A, Chilamkurthy S, Steiner B, Fang L, Bai J, Chintala S. PyTorch: an imperative style, high-performance deep learning library. In: Advances in Neural Information Processing Systems 32. 2019, 8024−8035

[5]	Wielemaker J, Schrijvers T, Triska M, Lager T. SWI-prolog. Theory and Practice of Logic Programming, 2012, 12(1−2): 67−96

[6]	Liu Y R, Hu Y Q, Qian H, Qian C, Yu Y . ZOOpt: a toolbox for derivative-free optimization. Science China Information Sciences, 2022, 65( 10): 207101

[7]	Manhaeve R, Dumancic S, Kimmig A, Demeester T, De Raedt L. DeepProblog: neural probabilistic logic programming. In: Advances in Neural Information Processing Systems 31. 2018, 3753−3763

[8]	Winters T, Marra G, Manhaeve R, De Raedt L. DeepStochLog: neural stochastic logic programming. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence. 2022, 10090−10100

[9]	Li Q, Huang S, Hong Y, Chen Y, Wu Y N, Zhu S C. Closed loop neural-symbolic learning via integrating neural perception, grammar parsing, and symbolic reasoning. In: Proceedings of the 37th International Conference on Machine Learning. 2020, 5884−5894