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Given the recent successes of Deep Learning in AI there has been increased interest in the role and need for explanations in machine learned theories.
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D. C. Berry and D. E. Broadbent · 1995
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J. R. Anderson, J. M. Fincham, and S. Douglass · 1997
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S. Stumpf, A. Bussone, and D. O’sullivan · 2016
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Transparency and explanation in deep reinforcement learning neural networks
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S. Muggleton, U. Schmid, C. Zeller, A. Tamaddoni-Nezhad, and T. Besold · 2018
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Summarizing agent strategies
O. Amir, F. Doshi-Velez, and D. Sarne · 2019
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Learning efficient logic programs
A. Cropper and S. H. Muggleton · 2019
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Ted: Teaching ai to explain its decisions
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T. Miller · 2019
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The teaching size: computable teachers and learners for universal languages
J. A. Telle, J. Hernández-Orallo, and C. Ferri · 2019
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Verbal explanations for deep reinforcement learning neural networks with attention on extracted features
X. Wang, S. Yuan, H. Zhang, M. Lewis, and K. Sycara · 2019
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Deep reinforcement learning with relational inductive biases
V. F. Zambaldi, D. C. Raposo, A. Santoro, V. Bapst, Y. Li, and I. e. a. Babuschkin · 2019
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Mutual explanations for cooperative decision making in medicine
U. Schmid and B. Finzel · 2020
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Interestingness elements for explainable reinforcement learning: Understanding agents’ capabilities and limitations
P. Sequeira and M. Gervasio · 2020
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