SymAware: A Software Development Framework for Trustworthy Multi-Agent Systems with Situational Awareness

TL;DR

SymAware provides a rich set of predefined data structures to compute, store, and communicate SA for agents, and 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.

Abstract

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.

Figures (7)

• Figure 1: A trustworthy warehouse, where the robots communicate awareness (described by regions and risk maps).
• Figure 2: SymAware's architecture conceptualized initially in kordabad2024robust.
• Figure 3: The simulation mechanism of SymAware, showcasing how the controller component of an agent updates its state. Events are triggered Before and after each updating step, allowing adding custom behavior via subscription.
• Figure 4: The asynchronous mode, where a context is switched when a coroutine is called by the await keyword, allowing other components to run without waiting for a long operation or loop.
• Figure 5: (a). the aircraft in the horizontal plane in the earth-fixed coordinate, where black variables are the state and the greens are the inputs. (b). The ownership (green) avoids the intruder (red) while both move toward their destinations.