%Aigaion2 BibTeX export von HES SO Valais Publications
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@ARTICLE{,
    author = {Calvaresi, Davide and Cid, Yashin Dicente and Marinoni, Mauro and Dragoni, Aldo Franco and Najjar, Amro and Schumacher, Michael},
  keywords = {Real-time multi-agent systems {\textperiodcentered} RT-MAS {\textperiodcentered} Timing predictability {\textperiodcentered} Timing reliability},
     month = feb,
     title = {Real‑time multi‑agent systems: rationality, formal model, and empirical results},
   journal = {Autonomous Agents and Multi-Agent Systems},
      year = {2021},
       doi = {https://doi.org/10.1007/s10458-020-09492-5},
  abstract = {Since its dawn as a discipline, Artificial Intelligence (AI) has focused on mimicking the
human mental processes. As AI applications matured, the interest for employing them into
real-world complex systems (i.e., coupling AI with Cyber-Physical Systems—CPS) kept
increasing. In the last decades, the multi-agent systems (MAS) paradigm has been among
the most relevant approaches fostering the development of intelligent systems. In numerous
scenarios, MAS boosted distributed autonomous reasoning and behaviors. However, many
real-world applications (e.g., CPS) demand the respect of strict timing constraints. Unfortunately, current AI/MAS theories and applications only reason “about time” and are incapable of acting “in time” guaranteeing any timing predictability. This paper analyzes the
MAS compliance with strict timing constraints (real-time compliance)—crucial for safety-critical applications such as healthcare, industry 4.0, and automotive. Moreover, it elicits
the main reasons for the lack of real-time satisfiability in MAS (originated from current
theories, standards, and implementations). In particular, traditional internal agent schedulers (general-purpose-like), communication middlewares, and negotiation protocols have
been identified as co-factors inhibiting real-time compliance. To pave the road towards
reliable and predictable MAS, this paper postulates a formal definition and mathematical model of real-time multi-agent systems (RT-MAS). Furthermore, this paper presents
the results obtained by testing the dynamics characterizing the RT-MAS model within the
simulator MAXIM-GPRT. Thus, it has been possible to analyze the deadline miss ratio
between the algorithms employed in the most popular frameworks and the proposed ones.
Finally, discussing the obtained results, the ongoing and future steps are outlined}
}