Fetching the paper…
Reading the bibliography…
Emerging applications in robotics and autonomous systems, such as autonomous driving and robotic surgery, often involve critical safety constraints that must be satisfied even when information about system models is limited.
J. N. Tsitsiklis, “Asynchronous stochastic approximation and q-learning,” Mach. Learn. , vol. 16, no. 3, pp. 185–202, 1994
1994
Earlier work this paper cites.
D. P. Bertsekas, Nonlinear Programming , 2nd ed. Belmont, MA, USA: Athena Scientific, 1999
1999
Earlier work this paper cites.
A. Abate, M. Prandini, J. Lygeros, and S. Sastry, “Probabilistic reachability and safety for controlled discrete time stochastic hybrid systems,” Automatica , vol. 44, no. 11, pp. 2724–2734, Nov 2008
2008
Earlier work this paper cites.
S. Summers and J. Lygeros, “Verification of discrete time stochastic hybrid systems: A stochastic reach-avoid decision problem,” Automatica , vol. 46, no. 12, pp. 1951–1961, 2010
2010
Earlier work this paper cites.
H. van Hasselt, “Double Q-learning,” in Adv. Neural Inf. Process. Syst. , 2010, pp. 2613–2621
2010
Earlier work this paper cites.
J. H. Gillula, G. M. Hoffmann, H. Huang, M. P. Vitus, and C. J. Tomlin, “Applications of hybrid reachability analysis to robotic aerial vehicles,” Int. J. Robot. Res. , vol. 30, no. 3, pp. 335–354, 2011
2011
Earlier work this paper cites.
E. Todorov, T. Erez, and Y. Tassa, “Mujoco: A physics engine for model-based control,” in 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems , 2012, pp. 5026–5033
2012
Earlier work this paper cites.
A. Majumdar, R. Vasudevan, M. M. Tobenkin, and R. Tedrake, “Convex optimization of nonlinear feedback controllers via occupation measures,” Int. J. Robot. Res. , vol. 33, no. 9, pp. 1209–1230, 2014
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
G. Piovan and K. Byl, “Reachability-based control for the active slip model,” Int. J. Robot. Res. , vol. 34, no. 3, pp. 270–287, 2015
2015
Earlier work this paper cites.
2015
Cited alongside, same era.
M. Turchetta, F. Berkenkamp, and A. Krause, “Safe exploration in finite markov decision processes with gaussian processes,” in Adv. Neural Inf. Process. Syst. , 2016, pp. 4312–4320
2016
Cited alongside, same era.
Y. Duan, X. Chen, R. Houthooft, J. Schulman, and P. Abbeel, “Benchmarking deep reinforcement learning for continuous control,” in Int. Conf. on Mach. Learn. , vol. 48, 2016, pp. 1329–1338
2016
Cited alongside, same era.
2016
Cited alongside, same era.
S. M. Richards, F. Berkenkamp, and A. Krause, “The Lyapunov neural network: Adaptive stability certification for safe learning of dynamical systems,” in Proc. 2nd Conf. on Robot Learn. , 2018, pp. 466–476
2018
Later among the works it cites.
L. Wang, E. A. Theodorou, and M. Egerstedt, “Safe learning of quadrotor dynamics using barrier certificates,” in Proc. IEEE Int. Conf. Robot. Autom. , 2018, pp. 2460–2465
2018
Later among the works it cites.
I. Yang, “A dynamic game approach to distributionally robust safety specifications for stochastic systems,” Automatica , vol. 94, pp. 94–101, 2018
2018
Later among the works it cites.
Y. Chow, O. Nachum, E. Duenez-Guzman, and M. Ghavamzadeh, “A Lyapunov-based approach to safe reinforcement learning,” in Adv. Neural Inf. Process. Syst. , 2018, pp. 8103–8112
2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
N. Malone, H. T. Chiang, K. Lesser, M. Oishi, and L. Tapia, “Hybrid dynamic moving obstacle avoidance using a stochastic reachable set-based potential field,” IEEE Trans. Robot. , vol. 33, no. 5, pp. 1124–1138, 2017
2017
Cited alongside, same era.
F. Berkenkamp, M. Turchetta, A. P. Schoellig, and A. Krause, “Safe model-based reinforcement learning with stability guarantees,” in Adv. Neural Inf. Process. Syst. , 2017
2017
Cited alongside, same era.
K. Lesser and M. Oishi, “Approximate safety verification and control of partially observable stochastic hybrid systems,” IEEE Trans. Automat. Contr. , vol. 62, no. 1, pp. 81–96, 2017
2017
Cited alongside, same era.
M. Chen, S. L. Herbert, M. S. Vashishtha, S. Bansal, and C. J. Tomlin, “A general system decomposition method for computing reachable sets and tubes,” IEEE Trans. Automat. Contr. , vol. 63, no. 11, pp. 3675–3688, 2018
2018
Cited alongside, same era.
J. F. Fisac, A. K. Akametalu, M. N. Zeilinger, S. Kaynama, J. Gillula, and C. J. Tomlin, “A general safety framework for learning-based control in uncertain robotic systems,” IEEE Trans. Automat. Contr. , vol. 64, no. 7, pp. 2737–2752, 2018
2018
Cited alongside, same era.
M. Alshiekh, R. Bloem, R. Ehlers, B. Könighofer, S. Niekum, and U. Topcu, “Safe reinforcement learning via shielding,” in Proc. AAAI Conf. on Artif. Intell. , 2018, pp. 2669–2678
2018
Later among the works it cites.
A. Wachi, Y. Sui, Y. Yue, and M. Ono, “Safe exploration and optimization of constrained MDPs using Gaussian processes,” in Proc. AAAI Conf. on Artif. Intell. , 2018, pp. 6548–6556
2018
Later among the works it cites.
J. F. Fisac, N. F. Lugovoy, V. Rubies-Royo, S. Ghosh, and C. Tomlin, “Bridging Hamilton-Jacobi safety analysis and reinforcement learning,” in Proc. IEEE Int. Conf. Robot. Autom. , 2019, pp. 8550–8556
2019
Later among the works it cites.
2019
Later among the works it cites.