通过引导一群看门狗人工智能代理对智能自治系统进行终身测试
Lifelong Testing of Smart Autonomous Systems by Shepherding a Swarm of Watchdog Artificial Intelligence Agents
摘要：
人工智能（AI）技术可以大致分为分析和自治。分析专注于提供感知，理解和预测从感官数据中收集的知识的算法。自主性围绕决策，并通过行动生产影响和塑造环境。智能自治系统（SAS）将分析和自治相结合，以自主理解、学习、决策和行动。要发挥作用，SAS必须值得信赖，这需要测试。SAS的终身学习使测试过程复杂化。在遥远的机会，它是可能的，以充分测试和认证的系统预发布，这在理论上是一个不可判定的问题，这是几乎不可能预测的未来行为，这些系统，单独或集体，将展示。虽然严格限制此类系统\textquoteright \学习能力以限制其行为的潜在不可预测性可能是可行的，但不期望的后果可能是严重限制其效用。在本文中，我们提出了一个看门狗AI（WAI）代理专用于SAS终身功能测试的体系结构。我们进一步提出了系统规范，包括一个抽象的层次，人类牧羊人的WAI代理群，以监督由人类和SAS的生态系统。讨论扩展到所提出的概念的挑战，优点和缺点。
英文摘要：
Artificial Intelligence (AI) technologies could be broadly categorised into Analytics and Autonomy. Analytics focuses on algorithms offering perception, comprehension, and projection of knowledge gleaned from sensorial data. Autonomy revolves around decision making, and influencing and shaping the environment through action production. A smart autonomous system (SAS) combines analytics and autonomy to understand, learn, decide and act autonomously. To be useful, SAS must be trusted and that requires testing. Lifelong learning of a SAS compounds the testing process. In the remote chance that it is possible to fully test and certify the system pre-release, which is theoretically an undecidable problem, it is near impossible to predict the future behaviours that these systems, alone or collectively, will exhibit. While it may be feasible to severely restrict such systems\textquoteright \ learning abilities to limit the potential unpredictability of their behaviours, an undesirable consequence may be severely limiting their utility. In this paper, we propose the architecture for a watchdog AI (WAI) agent dedicated to lifelong functional testing of SAS. We further propose system specifications including a level of abstraction whereby humans shepherd a swarm of WAI agents to oversee an ecosystem made of humans and SAS. The discussion extends to the challenges, pros, and cons of the proposed concept.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
