让大模型帮人把伦理原则转成可执行的机器人计划
Principles2Plan: LLM-Guided System for Operationalising Ethical Principles into Plans
- 人机协作生成符合伦理原则的可操作规则
- 专家提供原则，系统输出可被规划器使用的伦理规则
- 适合需要伦理决策的机器人系统研发者使用
机器人在人类环境中的运行需要具备伦理意识，但现有自动化规划工具支持不足。手动制定伦理规则耗时且高度依赖场景。我们提出 Principles2Plan，一个交互式研究原型，展示人类与大型语言模型（LLM）如何协同生成上下文相关的伦理规则，并指导自动化规划。领域专家提供规划领域、问题细节及高层原则（如利他与隐私）。系统生成符合这些原则的可操作伦理规则，用户可审查、排序后提供给规划器，生成具有伦理意识的计划。据我们所知，此前无系统支持在经典规划场景中生成基于原则的规则。Principles2Plan 展示了人-大模型协作在实现可实践伦理自动化规划中的潜力。
原文摘要 · Abstract (English)
Ethical awareness is critical for robots operating in human environments, yet existing automated planning tools provide little support. Manually specifying ethical rules is labour-intensive and highly context-specific. We present Principles2Plan, an interactive research prototype demonstrating how a human and a Large Language Model (LLM) can collaborate to produce context-sensitive ethical rules and guide automated planning. A domain expert provides the planning domain, problem details, and relevant high-level principles such as beneficence and privacy. The system generates operationalisable ethical rules consistent with these principles, which the user can review, prioritise, and supply to a planner to produce ethically-informed plans. To our knowledge, no prior system supports users in generating principle-grounded rules for classical planning contexts. Principles2Plan showcases the potential of human-LLM collaboration for making ethical automated planning more practical and feasible.
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