Self-Improving AI Agents Through Automated Skill Generation and Reinforcement Learning
This article examines how self-improving AI agents use automated skill generation and reinforcement learning to learn new skills, improve performance, and adapt to changing tasks. It explores key techniques, proposed architectures, challenges, and future research directions for developing intelligent, efficient, and autonomous AI systems.
Authors
- Smith Joe
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-13
- DOI
- https://doi.org/10.5281/zenodo.23340560
- Primary Topic
- Reinforcement Learning in Robotics
- Type
- preprint