agent/papers/items/2026-2607-05773-beyond-static-evaluation-building-simulation-environments-for-scalable-agentic-r.md

Paper: Beyond Static Evaluation: Building Simulation Environments for Scalable Agentic Reinforcement Learning

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type: paper title: "Beyond Static Evaluation: Building Simulation Environments for Scalable Agentic Reinforcement Learning" authors: Akshay Arora, Ishan Nigam, Ashutosh Aggarwal, Shefali Bansal, Krishna Singh, Sweta Kumari, Nikhil Mittal, Shariq Farhan, et al. year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.05773 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-07-07 updated_at: 2026-07-07 status: queued relevance: high topics:

• agent-evaluation
• computer-use
• tool-use
• world-model methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

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related_projects:

collection_score: 21 collection_queries: autonomous-agent-llm, tool-use, web-gui-agent

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: autonomous-agent-llm, tool-use, web-gui-agent
• inferred topics: agent-evaluation, computer-use, tool-use, world-model
• arXiv categories: cs.AI
• collection score: 21

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2607.05773