=Paper=
{{Paper
|id=Vol-2156/preface
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-2156/preface.pdf
|volume=Vol-2156
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==None==
<pdf width="1500px">https://ceur-ws.org/Vol-2156/preface.pdf</pdf>
<pre>
                                 Preface
    Since Artificial Intelligence applications became mature, there has been grow-
ing interest in applying them into complex real equipments, especially in order to
implement “Cyber-Physical Systems” (CPS). Unfortunately, most AI algorithms
are characterized by unpredictable or high-variance performances, making them
almost unusable for real-time control under hard deadlines.
    Recently some researches focused on tailoring AI techniques to make them
more predictable by explicitly reasoning “within and about” strict timing con-
straints (deadlines and precedence constraints between different tasks), but un-
fortunately, as far as we know, little effort has been spent to transfer these
approaches over Multi-Agents Systems (MAS), where additional constraints de-
riving from concurrent use of mutually exclusive resources hold (internal memory,
communication channels and peripherals such as sensors and actuators).
    MAS have always been a relevant topic within AI, since its very beginning,
and nowadays their technological advancements are leading to a concrete adop-
tion of decentralized systems with ever increasing connections, interactions, and
computational capabilities. Radically new challenges are arising for MAS from
the domains of the “Internet of Things” (IoT), CPS and “safety-critical” systems
but, unfortunately, in these regards MAS tend to reproduce the same myopic
approach of their parent discipline: high-quality of reasoning and human-like
interaction with little regard to concrete temporal and resources constraints. In
“safety-critical” systems MAS have not only to exhibit rational human-standard
behaviors, but they must also guarantee the completions of tasks within their
deadlines without violating priorities and precedences constraints in accessing
mutually exclusive resources.
    The 1st International Workshop on Real-Time compliant Multi-Agent Sys-
tems (RTcMAS) gathers contributions from both theoretical and pragmatic per-
spectives, targeting the employment of MAS in IoT and CPS through the ex-
ploitation of methodologies, algorithms and technologies from the Real-Time
Community. As such, RTcMAS has the potential to gather the attention of the
AI-interested audience from IJCAI-ECAI and AAMAS, with the goal of build-
ing the grounds for the next-generation Intelligent CPS, capable to face the
challenges of the “ever more connected” IoT era.


                                                          Davide Calvaresi1
                                                       Aldo Franco Dragoni2
                                                          Giorgio Buttazzo3

                                                 Co-chairs of RTcMAS 2018
   1
       University of Applied Sciences Western Switzerland, Switzerland
                             2
                               Università Politecnica delle Marche, Italy
                                     3
                                       Scuola Superiore Sant’Anna, Italy

</pre>