SymAware：面向具有态势感知的可信多智能体系统的软件开发框架
SymAware: A Software Development Framework for Trustworthy Multi-Agent Systems with Situational Awareness
AI总结：
针对多智能体系统中态势感知通信复杂导致难以开发可信系统的问题，提出新型仿真软件框架 SymAware，提供预定义数据结构与抽象接口以支持态势感知计算与控制，并通过专用组件提升实现效率，经三个案例验证有效。
摘要：
由于智能体之间态势感知（SA）的通信十分复杂，为实际应用开发可信的多智能体系统极具挑战。本文展示了一个名为 SymAware 的新型高效且易用的多智能体仿真软件框架，它提供了一组丰富的预定义数据结构，用于为智能体计算、存储和通信 SA。它还为智能体提供了一个抽象接口，使其在计算控制输入时能够考虑到周围智能体的态势感知、知识和风险。此外，利用一组专用组件，SymAware 将物理渲染和仿真引擎通信接口的繁重计算隐藏在控制线程之后，从而在弥合概念原型与实际应用之间的差距方面实现了很高的实现效率。本文使用三个多智能体案例研究验证了该软件框架的有效性和效率。
英文摘要：
Developing trustworthy multi-agent systems for practical applications is challenging due to the complicated communication of situational awareness (SA) among agents. This paper showcases a novel efficient and easy-to-use software framework for multi-agent simulation, named SymAware which provides a rich set of predefined data structures to compute, store, and communicate SA for agents. It also provides an abstract interface for the agents to compute their control inputs taking into account the awareness of the situation, knowledge, and risk of surrounding agents. Besides, utilizing a cluster of specialized components, SymAware hides the heavy computation of physical rendering and communication interfacing of simulation engines behind the control threads, resulting in high implementation efficiency in bridging the gap between conceptual prototyping and practical applications. Three multi-agent case studies are used to validate the efficacy and efficiency of this software framework.
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。
