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Scalable Planning with Deep Neural Network Learned Transition Models.

, , and . J. Artif. Intell. Res., (2020)

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Reward Potentials for Planning with Learned Neural Network Transition Models., , and . CP, volume 11802 of Lecture Notes in Computer Science, page 674-689. Springer, (2019)Compact and efficient encodings for planning in factored state and action spaces with learned Binarized Neural Network transition models., and . Artif. Intell., (2020)Robust Metric Hybrid Planning in Stochastic Nonlinear Domains Using Mathematical Optimization.. ICAPS, page 375-383. AAAI Press, (2023)A Unified Framework for Planning with Learned Neural Network Transition Models.. AAAI, page 5016-5024. AAAI Press, (2021)Scalable Planning with Tensorflow for Hybrid Nonlinear Domains., , and . NIPS, page 6273-6283. (2017)Training Experimentally Robust and Interpretable Binarized Regression Models Using Mixed-Integer Programming., , and . CoRR, (2021)Mathematical Programming Models for Optimizing Partial-Order Plan Flexibility., , and . ECAI, volume 285 of Frontiers in Artificial Intelligence and Applications, page 1044-1052. IOS Press, (2016)Training Experimentally Robust and Interpretable Binarized Regression Models Using Mixed-Integer Programming., , and . SSCI, page 838-845. IEEE, (2022)Rapid Identification of Protein Formulations with Bayesian Optimisation., , , , , and . ICMLA, page 776-781. IEEE, (2023)Scalable Nonlinear Planning with Deep Neural Network Learned Transition Models., , and . CoRR, (2019)