AI 中文总结
针对自主智能体去中心化协调中存在的策略不兼容、角色难区分等问题，提出意见引导分层策略，通过非线性意见动力学实现无通信协调，可打破对称性，在一般和博弈中能保证智能体达成均衡。
AI 中文摘要
自主智能体越来越多地与其他独立智能体交互，这类交互通常允许多种联合行为。当两个智能体偏好不同的联合行为时，它们的独立策略可能相互不兼容，无法达成协调结果；当它们偏好相同时，在需要时无法区分各自的角色。理想情况下，智能体应能与遇到的任何智能体协调，无论该智能体旨在实现哪种可接受的联合行为。为此，我们提出一种新型策略——意见引导策略，该策略保留所有可接受的联合行为，将选择推迟到执行阶段，此时对方智能体的行为会揭示应实现的联合行为。为实现这一点，我们在分层实现中利用非线性意见动力学，引导智能体根据对方的动态行为达成共同的可接受联合行为，即使无需通信。我们正式确定了该策略对对方智能体可能持有的每种偏好都保持鲁棒性的条件。这种鲁棒性具有重要意义：运行相同策略的两个智能体可在需要时打破对称性，这是传统策略所缺乏的能力。跨不同应用的三个案例研究表明，意见引导策略能与每个随机遇到的智能体协调，只要该智能体愿意实现其中一种可接受的联合行为。其中一个案例对应一般和博弈：与传统方法致力于提前找到唯一纳什均衡不同，意见引导策略保留所有均衡的开放性，并保证智能体通过运行时交互达成由交互决定的某一均衡。
英文摘要
Autonomous agents increasingly interact with other independent agents, and such interactions typically admit multiple joint behaviors. When two agents prefer different ones, their independent strategies may be mutually incompatible and fail to reach a coordinated outcome; when they are identical, neither can differentiate its role when needed. Ideally, an agent should coordinate with any agent it encounters, regardless of which admissible joint behavior that agent aims to realize. We therefore propose a new form of strategy, the opinion-guided strategy, which keeps all the admissible joint behaviors available and postpones the selection to execution time, when the other agent's behavior reveals which one to realize. To realize this, nonlinear opinion dynamics are leveraged in a layered realization to guide the agent to a common admissible joint behavior in response to the other agent's evolving behavior, even without communication. We formally establish the conditions under which the strategy remains robust to every preference the other agent may hold. This robustness has an important implication: two agents running identical strategies can break symmetry when needed, a capability that conventional strategies lack. Three case studies across different applications show that the opinion-guided strategy coordinates with every randomly encountered agent, as long as it is willing to realize one of the admissible joint behaviors. One of them corresponds to a general-sum game: unlike conventional approaches devoted to finding a unique Nash equilibrium in advance, the opinion-guided strategy keeps every equilibrium open and guarantees the agents reach one, decided by their runtime interaction.
