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Found 7 papers, 1 papers with code
Push- and Pull-based Effective Communication in Cyber-Physical Systems
In Cyber Physical Systems (CPSs), two groups of actors interact toward the maximization of system performance: the sensors, observing and disseminating the system state, and the actuators, performing physical decisions based on the received information.
Fast Context Adaptation in Cost-Aware Continual Learning
This creates friction: on the one hand, the learning process needs resources to quickly convergence to an effective strategy; on the other hand, the learning process needs to be efficient, i. e., take as few resources as possible from the user's data plane, so as not to throttle users' QoS.
Multi-Agent Reinforcement Learning for Pragmatic Communication and Control
In this work, we propose a joint design that combines goal-oriented communication and networked control into a single optimization model, an extension of a multiagent POMDP which we call Cyber-Physical POMDP (CP-POMDP).
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Towards Decentralized Predictive Quality of Service in Next-Generation Vehicular Networks
To ensure safety in teleoperated driving scenarios, communication between vehicles and remote drivers must satisfy strict latency and reliability requirements.
Artificial Intelligence in Vehicular Wireless Networks: A Case Study Using ns-3
Artificial intelligence (AI) techniques have emerged as a powerful approach to make wireless networks more efficient and adaptable.
A Reinforcement Learning Framework for PQoS in a Teleoperated Driving Scenario
In recent years, autonomous networks have been designed with Predictive Quality of Service (PQoS) in mind, as a means for applications operating in the industrial and/or automotive sectors to predict unanticipated Quality of Service (QoS) changes and react accordingly.
Distributed Reinforcement Learning for Flexible and Efficient UAV Swarm Control
The proposed framework relies on the possibility for the UAVs to exchange some information through a communication channel, in order to achieve context-awareness and implicitly coordinate the swarm's actions.
