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<h4 class="classic-title"><span>Real-Time Multi-Agent Systems</span></h4>
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<p style="text-align: justify;">Since Artificial Intelligence applications became mature, there has been growing interest in applying them into complex systems and physical equipments, especially in Cyber-Physical Systems (CPS) scenarios. Unfortunately, most AI algorithms are characterized by unpredictable or high-variance performances, making them unsuitable for real-time control under hard deadlines.<br>
Recently, research has been conducted on tailoring AI techniques to make them more predictable by explicitly reasoning “within and about” strict timing constraints (deadlines and precedence constraints between different tasks). However, little effort has been spent to transfer these approaches over Multi-Agents Systems (MAS) where additional constraints deriving from concurrent use of mutually exclusive resources stand (e.g. internal memory, communication channels, and peripherals such as sensors and actuators).
MAS have been a relevant topic within AI since its very beginning, and their technological advancements lead to a concrete adoption of decentralized flexible systems with increasing connections, interactions, and computational capabilities. Today radically new challenges are arising from the domains of the “Internet of Things” (IoT), CPS and “safety-critical” systems.<br>
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 attention to concrete temporal and resources constraints. In “safety-critical” systems, MAS should not only exhibit rational human-standard behaviors, they must also guarantee the completions of tasks within their deadlines without violating priorities and precedences constraints in accessing mutually exclusive resources. Furthermore, since agents interact, negotiate resources and exchange executions of tasks in a social manner, real-time guarantees should not only be provided at the level of each single agent but they should also be evaluated at the level of the "emergent behaviour" of the entire Agency, and this last vision is quite challenging from a theoretical point of view.
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<h4 class="classic-title"><span>Wriggle Solutions - SMART Tyre</span></h4>
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<p>Composed of multidisciplinary experts, the team is determined to disrupt the tyres market with innovative features that will guarantee still unmatched safety standards.
<br><br>
<a href="http://www.wrigglesolutions.com" target="_blank" class="btn-system btn-medium">Read More</a>
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<p>To appear soon...
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