发表机构
Scuola Superiore Meridionale; Macquarie University; University of Salerno（南方高等学校; 麦考瑞大学; 萨勒诺大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种基于自由能原理的控制框架，通过手势将人类偏好在线整合进智能体策略，并在巡逻车人机交互实验中验证了交互调节的有效性。
AI 中文摘要
控制与学习领域的一个核心挑战是设计调节人类与自主智能体之间交互的机制。受计算神经科学中自由能原理的启发，我们引入了一个控制理论框架，将人类偏好在线整合到智能体策略中。我们将该框架转化为一个开放控制架构，并使用一个涉及通过机载传感导航的巡逻车的人机交互实验平台来验证我们的方法。远程操作员配备虚拟现实头显，与巡逻车共享相同的传感信息。人类偏好通过手势提供给巡逻车，这些手势在智能体目标与偏好之间引入了合作与竞争两种交互。实验表明，交互得到了有效调节，验证了所提出方法的有效性。
英文摘要
A central challenge across control and learning is the design of mechanisms regulating the interactions between humans and autonomous agents. Inspired by the free energy principle from computational neuroscience, we introduce a control-theoretical framework to integrate human preferences online into an agent policy. We turn the framework into an open control architecture and validate our approach using a human-in-the-loop experimental testbed involving a rover navigating via onboard sensing. The human, remotely located and equipped with virtual reality headsets, shares the same sensory information as the rover. Human preferences are provided to the rover via gestures which introduce both cooperative and competitive interactions between the agent goal and the preferences. The experiments show that interactions are regulated, validating the proposed approach.
CommentsAccepted for presentation to IEEE Conference on Decision and Control 2026, Honolulu (USA)
