Developing AI Agents with Simulated Data: Why, what, and how?
每日信息看板 · 2026-02-17
2026-02-17T18:53:27Z
Published
AI 总结
As insufficient data volume and quality remain the key impediments to the adoption of modern subsymbolic AI, techniques of synthetic data generation are in hig…
- As insufficient data volume and quality remain the key impediments to the adoption of modern subsymbolic AI, techniques of synthetic data g…
- Simulation offers an apt, systematic approach to generating diverse synthetic data
- This chapter introduces the reader to the key concepts, benefits, and challenges of simulation-based synthetic data generation for AI train…
#arXiv #paper #研究/论文 #Agent
内容摘录
As insufficient data volume and quality remain the key impediments to the adoption of modern subsymbolic AI, techniques of synthetic data generation are in high demand. Simulation offers an apt, systematic approach to generating diverse synthetic data. This chapter introduces the reader to the key concepts, benefits, and challenges of simulation-based synthetic data generation for AI training purposes, and to a reference framework to describe, design, and analyze digital twin-based AI simulation solutions.