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Scientific Discovery and the Cost of Measurement - Balancing Information and Cost in Reinforcement Learning.

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Optimizing thermodynamic trajectories using evolutionary reinforcement learning., , , , , и . CoRR, (2019)Learning to grow: control of materials self-assembly using evolutionary reinforcement learning., и . CoRR, (2019)Sampling algorithms for validation of supervised learning models for Ising-like systems., и . J. Comput. Phys., (2017)Active Measure Reinforcement Learning for Observation Cost Minimization., , , и . CoRR, (2020)Scientific intuition inspired by machine learning generated hypotheses., , , и . CoRR, (2020)Finding the ground state of spin Hamiltonians with reinforcement learning., , и . Nat. Mach. Intell., 2 (9): 509-517 (2020)Reinforcement Learning in a Physics-Inspired Semi-Markov Environment., , , и . Canadian AI, том 12109 из Lecture Notes in Computer Science, стр. 55-66. Springer, (2020)Balancing Information with Observation Costs in Deep Reinforcement Learning., , , и . Canadian AI, Canadian Artificial Intelligence Association, (2022)Weakly-supervised multi-class object localization using only object counts as labels., и . CoRR, (2021)Dynamical large deviations of two-dimensional kinetically constrained models using a neural-network state ansatz., , , и . CoRR, (2020)