{"slug": "environments-as-scaffold-enriching-feedback-to-bootstrap-self-evolving-agents-in", "title": "Environments as Scaffold: Enriching Feedback to Bootstrap Self-Evolving Agents in Long-Horizon Tasks", "summary": "Researchers propose a novel framework that enriches feedback by using environments as scaffolds to bootstrap self-evolving agents in long-horizon tasks, addressing reward sparsity in reinforcement learning for large language models. The approach aims to improve autonomous agent training beyond conventional supervised fine-tuning.", "body_md": "Large Language Models demonstrate remarkable proficiency in static reasoning, yet training them as autonomous agents through Reinforcement Learning (RL) for long-horizon tasks is often hindered by severe reward sparsity. While conventional agent-side warming up via supervised fine-tuning (SFT) can a", "url": "https://wpnews.pro/news/environments-as-scaffold-enriching-feedback-to-bootstrap-self-evolving-agents-in", "canonical_source": "https://aiflash.com/news/116092/", "published_at": "2026-09-09 04:00:04+00:00", "updated_at": "2026-09-09 04:20:46.597794+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "large-language-models", "ai-research", "ai-agents"], "entities": [], "alternates": {"html": "https://wpnews.pro/news/environments-as-scaffold-enriching-feedback-to-bootstrap-self-evolving-agents-in", "markdown": "https://wpnews.pro/news/environments-as-scaffold-enriching-feedback-to-bootstrap-self-evolving-agents-in.md", "text": "https://wpnews.pro/news/environments-as-scaffold-enriching-feedback-to-bootstrap-self-evolving-agents-in.txt", "jsonld": "https://wpnews.pro/news/environments-as-scaffold-enriching-feedback-to-bootstrap-self-evolving-agents-in.jsonld"}}