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Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time
  Reinforcement Learning
v1v2 (latest)

Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning

International Conference on Machine Learning (ICML), 2022
24 May 2022
Harley Wiltzer
David Meger
Marc G. Bellemare
ArXiv (abs)PDFHTML

Papers citing "Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning"

9 / 9 papers shown
Phase Diagram of Dropout for Two-Layer Neural Networks in the Mean-Field Regime
Phase Diagram of Dropout for Two-Layer Neural Networks in the Mean-Field Regime
Lénaic Chizat
Pierre Marion
Yerkin Yesbay
105
0
0
08 Oct 2025
Continuous-Time Value Iteration for Multi-Agent Reinforcement Learning
Continuous-Time Value Iteration for Multi-Agent Reinforcement Learning
Xuefeng Wang
Lei Zhang
Henglin Pu
Ahmed H. Qureshi
Husheng Li
187
0
0
11 Sep 2025
A Temporal Difference Method for Stochastic Continuous Dynamics
A Temporal Difference Method for Stochastic Continuous Dynamics
Haruki Settai
Naoya Takeishi
Takehisa Yairi
524
0
0
21 May 2025
Tractable Representations for Convergent Approximation of Distributional HJB Equations
Julie Alhosh
Harley Wiltzer
David Meger
106
1
0
07 Mar 2025
Parabolic Continual LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Haoming Yang
Ali Hasan
Vahid Tarokh
246
1
0
03 Mar 2025
Action Gaps and Advantages in Continuous-Time Distributional
  Reinforcement Learning
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2024
Harley Wiltzer
Marc G. Bellemare
David Meger
Patrick Shafto
Yash Jhaveri
167
3
0
14 Oct 2024
Actor-Critic Methods using Physics-Informed Neural Networks: Control of
  a 1D PDE Model for Fluid-Cooled Battery Packs
Actor-Critic Methods using Physics-Informed Neural Networks: Control of a 1D PDE Model for Fluid-Cooled Battery Packs
Amartya Mukherjee
Jun Liu
126
2
0
18 May 2023
Bridging Physics-Informed Neural Networks with Reinforcement Learning:
  Hamilton-Jacobi-Bellman Proximal Policy Optimization (HJBPPO)
Bridging Physics-Informed Neural Networks with Reinforcement Learning: Hamilton-Jacobi-Bellman Proximal Policy Optimization (HJBPPO)
Amartya Mukherjee
Jun Liu
184
17
0
01 Feb 2023
Decision-making with Speculative Opponent Models
Decision-making with Speculative Opponent ModelsIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Jing-rong Sun
Shuo Chen
Cong Zhang
Yining Ma
Jie Zhang
233
2
0
22 Nov 2022
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