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Stochastic Shortest Path with Adversarially Changing Costs

Stochastic Shortest Path with Adversarially Changing Costs

20 June 2020
Aviv A. Rosenberg
Yishay Mansour
    AAML
ArXivPDFHTML

Papers citing "Stochastic Shortest Path with Adversarially Changing Costs"

8 / 8 papers shown
Title
MetaCURL: Non-stationary Concave Utility Reinforcement Learning
MetaCURL: Non-stationary Concave Utility Reinforcement Learning
B. Moreno
Margaux Brégère
Pierre Gaillard
Nadia Oudjane
OffRL
37
0
0
30 May 2024
Layered State Discovery for Incremental Autonomous Exploration
Layered State Discovery for Incremental Autonomous Exploration
Liyu Chen
Andrea Tirinzoni
A. Lazaric
Matteo Pirotta
28
0
0
07 Feb 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear
  Function Approximation
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation
Uri Sherman
Tomer Koren
Yishay Mansour
32
12
0
30 Jan 2023
Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear
  Contextual Bandits and Markov Decision Processes
Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes
Chen Ye
Wei Xiong
Quanquan Gu
Tong Zhang
23
29
0
12 Dec 2022
Dynamic Regret of Online Markov Decision Processes
Dynamic Regret of Online Markov Decision Processes
Peng Zhao
Longfei Li
Zhi-Hua Zhou
OffRL
22
17
0
26 Aug 2022
Convex duality for stochastic shortest path problems in known and
  unknown environments
Convex duality for stochastic shortest path problems in known and unknown environments
Kelli Francis-Staite
19
0
0
31 Jul 2022
Learning Stochastic Shortest Path with Linear Function Approximation
Learning Stochastic Shortest Path with Linear Function Approximation
Steffen Czolbe
Jiafan He
Adrian V. Dalca
Quanquan Gu
36
30
0
25 Oct 2021
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and
  Known Transition
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition
Liyu Chen
Haipeng Luo
Chen-Yu Wei
21
32
0
07 Dec 2020
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