Programmatic policies for interpretable reinforcement learning using pre-trained models

• 主要作者: Tu, Xia Yang
• 其他作者: Arvind Easwaran
• 格式: Final Year Project
• 語言: English
• 出版: Nanyang Technological University 2024
• 主題: Computer and Information Science; LLM; Reinforcement learning
• 在線閱讀: https://hdl.handle.net/10356/181169

Decision Trees (DTs) are widely used in machine learning due to their critical interpretability. However, training DTs in a Reinforcement Learning (RL) setting is challenging. In the project, we present a framework to improve the interpretability of reinforcement learning (RL) by generating prog...