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Publications about 'Safe exploration'
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D. Ding.
Provable reinforcement learning for constrained and multi-agent control systems.
PhD thesis,
University of Southern California,
2022.
Keyword(s): Constrained Markov decision processes,
Constrained nonconvex optimization,
Function approximation,
Game-agnostic convergence,
Multi-agent reinforcement learning,
Multi-agent systems,
Natural policy gradient,
Policy gradient methods,
Proximal policy optimization,
Primal-dual algorithms,
Reinforcement learning,
Safe exploration,
Safe reinforcement learning,
Sample complexity,
Stochastic optimization.
[bibtex-entry]
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D. Ding,
X. Wei,
Z. Yang,
Z. Wang,
and M. R. Jovanovic.
Provably efficient safe exploration via primal-dual policy optimization.
In 24th International Conference on Artificial Intelligence and Statistics,
volume 130,
Virtual,
pages 3304-3312,
2021.
Keyword(s): Safe reinforcement learning,
Constrained Markov decision processes,
Safe exploration,
Proximal policy optimization,
Non-convex optimization,
Online mirror descent,
Primal-dual method.
[bibtex-entry]
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Last modified: Sat Oct 5 22:00:41 2024
Author: mihailo.
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