用智能代理自动演化硬件设计代码，实现全流程无人干预。
Agentic Hardware Design as Repository-Level Code Evolution
- 将硬件设计视为代码仓库的持续演化，通过代理自动管理版本和状态。
- 在多个基准测试中达成100%完成率，全程无需人工介入。
- 适合芯片设计自动化研究者，推动AI在硬件工程中的深度应用。
我们提出HORIZON，一个自演化智能体框架，将硬件设计视为仓库级别的代码演进。通过将Markdown脚本编译为包含领域知识、可执行评估器、验收条件和git/运行时策略的项目包，一个无手操作的智能体循环在隔离的git工作树中持续演化。该方法将以往仅限于EDA软件系统的仓库级自演化扩展至硬件设计本身。我们在ChipBench、RTLLM、Verilog-Eval及九类CVDP类别上评估，所有测试套件均实现100%完成率，且全程保持完全无人干预。然而，我们不认为硬件设计的智能体问题已解决：这些基准仅为芯片设计广阔工程挑战的受控代理。第~\ref{sec:discuss}节分析当前研究局限，并指出开放性研究挑战。
原文摘要 · Abstract (English)
We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution. A Markdown harness is compiled into a project pack containing domain knowledge, an executable evaluator, an acceptance predicate, and a git/runtime policy; a hands-free agent loop then evolves an isolated git worktree, using repository operations for state management, tracing, and replay. This extends prior works of repository-scale self-evolution from EDA software systems, to hardware-design artifacts themselves. We evaluate our approach on ChipBench, RTLLM, Verilog-Eval, and nine CVDP categories, achieving 100\% benchmark completion across all suites with a fully hands-free agentic loop. However, we do not claim that agentic AI for hardware design is solved: these benchmarks are controlled proxies for a much broader engineering problem in chip design. Section~\ref{sec:discuss} examines the limitations of the current study and highlights open research challenges.
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