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2020 – today
- 2022
[i6]Chris Nota:
On the Convergence of Discounted Policy Gradient Methods. CoRR abs/2212.14066 (2022)- 2021
- [c4]Chris Nota, Philip S. Thomas, Bruno C. da Silva:
Posterior Value Functions: Hindsight Baselines for Policy Gradient Methods. ICML 2021: 8238-8247 - 2020
- [c3]Yash Chandak, Georgios Theocharous, Chris Nota, Philip S. Thomas:
Lifelong Learning with a Changing Action Set. AAAI 2020: 3373-3380 - [c2]Chris Nota, Philip S. Thomas:
Is the Policy Gradient a Gradient? AAMAS 2020: 939-947 - [c1]James E. Kostas, Chris Nota, Philip S. Thomas:
Asynchronous Coagent Networks. ICML 2020: 5426-5435 - [i5]Francisco M. Garcia, Chris Nota, Philip S. Thomas:
Learning Reusable Options for Multi-Task Reinforcement Learning. CoRR abs/2001.01577 (2020)
2010 – 2019
- 2019
- [i4]James E. Kostas, Chris Nota, Philip S. Thomas:
Asynchronous Coagent Networks: Stochastic Networks for Reinforcement Learning without Backpropagation or a Clock. CoRR abs/1902.05650 (2019) - [i3]Yash Chandak, Georgios Theocharous, Chris Nota, Philip S. Thomas:
Lifelong Learning with a Changing Action Set. CoRR abs/1906.01770 (2019) - [i2]Philip S. Thomas, Scott M. Jordan, Yash Chandak, Chris Nota, James E. Kostas:
Classical Policy Gradient: Preserving Bellman's Principle of Optimality. CoRR abs/1906.03063 (2019) - [i1]Chris Nota, Philip S. Thomas:
Is the Policy Gradient a Gradient? CoRR abs/1906.07073 (2019)
Coauthor Index
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