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Evaluation of deep reinforcement learning (RL) is inherently challenging.
Reinforcement learning - an introduction
Richard S. Sutton and Andrew G. Barto · 1998
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Software testing and analysis - process, principles and techniques
Mauro Pezzè and Michal Young · 2007
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The mario AI benchmark and competitions
Sergey Karakovskiy and Julian Togelius · 2012
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The arcade learning environment: An evaluation platform for general agents
Marc G. Bellemare, Yavar Naddaf, Joel Veness, and Michael Bowling · 2013
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Learning nondeterministic Mealy machines
Ali Khalili and Armando Tacchella · 2014
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A comprehensive survey on safe reinforcement learning
Javier Garcıa and Fernando Fernández · 2015
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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Mastering the game of Go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al · 2016
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Formal verification of piece-wise linear feed-forward neural networks
Rüdiger Ehlers · 2017
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Verification and repair of control policies for safe reinforcement learning
Shashank Pathak, Luca Pulina, and Armando Tacchella · 2017
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Safe reinforcement learning via shielding
Mohammed Alshiekh, Roderick Bloem, Rüdiger Ehlers, Bettina Könighofer, Scott Niekum, and Ufuk Topcu · 2018
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Deep reinforcement fuzzing
Konstantin Böttinger, Patrice Godefroid, and Rishabh Singh · 2018
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FuzzerGym: A competitive framework for fuzzing and learning
William Drozd and Michael D. Wagner · 2018
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DeepGauge: multi-granularity testing criteria for deep learning systems
Lei Ma, Felix Juefei-Xu, Fuyuan Zhang, Jiyuan Sun, Minhui Xue, Bo Li, Chunyang Chen, Ting Su, Li Li, Yang Liu, Jianjun Zhao, and Yadong Wang · 2018
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Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, et al · 2018
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DeepTest: automated testing of deep-neural-network-driven autonomous cars
Yuchi Tian, Kexin Pei, Suman Jana, and Baishakhi Ray · 2018
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Joshua Achiam and Dario Amodei · 2019
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Mengshi Zhang, Yuqun Zhang, Lingming Zhang, Cong Liu, and Sarfraz Khurshid · 2020
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Deep reinforcement learning at the edge of the statistical precipice
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C Courville, and Marc Bellemare · 2021
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Formal verification of neural networks for safety-critical tasks in deep reinforcement learning
Davide Corsi, Enrico Marchesini, and Alessandro Farinelli · 2021
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Deep reinforcement learning for autonomous driving: A survey
B Ravi Kiran, Ibrahim Sobh, Victor Talpaert, Patrick Mannion, Ahmad A Al Sallab, Senthil Yogamani, and Patrick Pérez · 2021
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The art, science, and engineering of fuzzing: A survey
Valentin J. M. Manès, HyungSeok Han, Choongwoo Han, Sang Kil Cha, Manuel Egele, Edward J. Schwartz, and Maverick Woo · 2021
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DeepXplore: automated whitebox testing of deep learning systems
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Ijon: Exploring deep state spaces via fuzzing
Cornelius Aschermann, Sergej Schumilo, Ali Abbasi, and Thorsten Holz · 2020
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Is neuron coverage a meaningful measure for testing deep neural networks?
Fabrice Harel-Canada, Lingxiao Wang, Muhammad Ali Gulzar, Quanquan Gu, and Miryung Kim · 2020
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The NetHack Learning Environment
Heinrich Küttler, Nantas Nardelli, Alexander H. Miller, Roberta Raileanu, Marco Selvatici, Edward Grefenstette, and Tim Rocktäschel · 2020
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Mastering atari, go, chess and shogi by planning with a learned model
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Does neuron coverage matter for deep reinforcement learning?: A preliminary study
Miller Trujillo, Mario Linares-Vásquez, Camilo Escobar-Velásquez, Ivana Dusparic, and Nicolás Cardozo · 2020
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Adaptive shielding under uncertainty
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Banditfuzz: Fuzzing SMT solvers with multi-agent reinforcement learning
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Syzvegas: Beating kernel fuzzing odds with reinforcement learning
Daimeng Wang, Zheng Zhang, Hang Zhang, Zhiyun Qian, Srikanth V. Krishnamurthy, and Nael B. Abu-Ghazaleh · 2021
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Train a mario-playing RL agent
Yuansong Feng, Suraj Subramanian, Howard Wang, and Steven Guo · 2022
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Nyx-net: network fuzzing with incremental snapshots
Sergej Schumilo, Cornelius Aschermann, Andrea Jemmett, Ali Abbasi, and Thorsten Holz · 2022
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The Fuzzing Book
Andreas Zeller, Rahul Gopinath, Marcel Böhme, Gordon Fraser, and Christian Holler · 2022
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