Browsing by Subject Reinforcement Learning
Showing results 1 to 14 of 14
| Issue Date | Title | Author(s) |
| 2024 | Language Agents: From Next-Token Prediction to Digital Automation | Yao, Shunyu |
| 2022 | Learning Algorithms for Intelligent Agents and Mechanisms | Rahme, Jad |
| 2022 | Learning from Humans: Beyond Classical Imitation Learning | Spencer, Jonathan Cullinan |
| 2018 | Learning Neural Representations That Support Efficient Reinforcement Learning | Stachenfeld, Kimberly Lauren |
| 2023 | Learning Through Social Interactions and Learning to Socially Interact in Multi-Agent Learning | Madhushani, Udari |
| 2022 | Multi-Agent Sequential Decision Modeling for Information Collection and Intervention in Epidemics and Wildfires | Thul, Lawrence A |
| 2022 | Overcoming Sampling and Exploration Challenges in Deep Reinforcement Learning | Simmons-Edler, Riley |
| 2021 | Primal-Dual Method for Reinforcement Learning and Markov Decision Processes | Gong, Hao |
| 2023 | Principles and Applications of Discrete Deep Generative Models | Fan, Ting-Han |
| 2022 | Provable Reinforcement Learning with Constraints and Function Approximation | Mir Yoosefi, Seyed Sobhan |
| 2024 | Rethinking Prediction Errors in Dopaminergic Signals in the Brain | Lee, Rachel Stephanie |
| 2024 | SketchProbe: Discovering Vulnerabilities in Sketch-based Applications with Reinforcement Learning | Luo, Wei |
| 2022 | Topics in the Statistical and Computational Complexities of Modern Machine Learning | Yang, Zhuoran |
| 2022 | Towards Efficient and Effective Deep Model-based Reinforcement Learning | Luo, Yuping |