← Back to papers
2024 JMLR JMLR 2024

Policy Gradient Methods in the Presence of Symmetries and State Abstractions

Abstract

Prakash Panangaden, Sahand Rezaei-Shoshtari, Rosie Zhao, David Meger, Doina Precup; 25(71):1−57, 2024.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning and Reinforcement Learning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Prakash Panangaden , Sahand Rezaei-Shoshtari , Rosie Zhao , David Meger , Doina Precup

Topics

Artificial Intelligence > Core AI > Planning Machine Learning > Core Methods > Representation Learning Reinforcement Learning > Methods > Policy Learning Artificial Intelligence > Core AI > Reasoning

Keywords

state abstraction policy gradient continuous control
Download PDF

Related papers

On the Effect of Initialization: The Scaling Path of 2-Layer Neural Networks 2024
Convergence for nonconvex ADMM, with applications to CT imaging 2024
Functional Directed Acyclic Graphs 2024
Sum-of-norms clustering does not separate nearby balls 2024
Decentralized Natural Policy Gradient with Variance Reduction for Collaborative Multi-Agent Reinforcement Learning 2024