We describe ACE0, a lightweight platform for evaluating the suitability and viability of AI methods for behaviour discovery in multiagent simulations. Specifically, ACE0 was designed to explore AI methods for multi-agent simulations used in operations research studies related to new technologies such as autonomous aircraft. Simulation environments used in production are often high-fidelity, complex, require significant domain knowledge and as a result have high R&D costs. Minimal and lightweight simulation environments can help researchers and engineers evaluate the viability of new AI technologies for behaviour discovery in a more agile and potentially cost effective manner. In this paper we describe the motivation for the development of ACE0.We provide a technical overview of the system architecture, describe a case study of behaviour discovery in the aerospace domain, and provide a qualitative evaluation of the system. The evaluation includes a brief description of collaborative research projects with academic partners, exploring different AI behaviour discovery methods.
翻译:我们描述ACE0,这是一个用于评价AI在多试剂模拟中的行为发现方法是否适当和可行的轻量级平台,具体地说,ACE0旨在探索AI在与自主飞机等新技术有关的操作研究中使用的多试剂模拟方法,生产中使用的模拟环境往往非常虚伪、复杂、需要大量领域知识,因此研发成本很高。最小和轻量级模拟环境可以帮助研究人员和工程师以更灵活和具有潜在成本效益的方式评估AI新技术在行为发现方面的可行性。我们在本文件中描述了ACE0的开发动机。我们提供了系统结构的技术概览,描述了在航空航天领域的行为发现案例研究,并对系统进行了定性评价。评价包括简要描述与学术伙伴的合作研究项目,探讨不同的AI行为发现方法。