Real-Time Multi-Agent Systems: challenges, model, and performance analysis

Since its dawn as a discipline, Artificial Intelligence (AI) has focused on mimicking the human mental processes. Maturing, the AI applications have been increasingly employed into real-world complex systems (i.e., coupling AI with Cyber-Physical Systems - CPS). Recently, the Multi-Agent Systems (MAS) paradigm has been among the most relevant approaches fostering the development of intelligent systems (IS), boosting distributed autonomous reasoning and behaviors. However, many real-world applications (e.g., CPS) demand compliance with strict timing constraints. Unfortunately, current AI/MAS theories and applications only reason ``about time'' and are incapable of acting ``in time'', thus failing to guarantee any timing predictability.
This presentation will introduce the audience to the analyzes of MAS and compliance with strict timing constraints (real-time compliance), spanning from the lack of real-time satisfiability (originated from current theories, standards, and implementations), to pave the road towards reliable and predictable MAS postulating a formal definition and mathematical model of Real-Time Multi-Agent Systems (RT-MAS).