A5015248763- Reinforcement Learning in Robotics
- Advanced Neural Network Applications
- IoT and Edge/Fog Computing
- Simulation Techniques and Applications
- Advanced Control Systems Optimization
- Fault Detection and Control Systems
- Cloud Computing and Resource Management
- Real-Time Systems Scheduling
- Autonomous Vehicle Technology and Safety
- Embedded Systems Design Techniques
- Traffic Prediction and Management Techniques
- Maritime Navigation and Safety
- Anomaly Detection Techniques and Applications
- Video Surveillance and Tracking Methods
- Building Energy and Comfort Optimization
- Transportation Planning and Optimization
- Vehicular Ad Hoc Networks (VANETs)
- Evolutionary Algorithms and Applications
- Traffic control and management
- Software System Performance and Reliability
- Machine Learning and Data Classification
- Context-Aware Activity Recognition Systems
- Smart Grid Energy Management
- Parallel Computing and Optimization Techniques
- Air Quality Monitoring and Forecasting
University of Antwerp
2013-2025
Ghent University Hospital
2023
IMEC
2020
Mississippi State University
2020
The University of Texas at Dallas
2020
Université de Toulouse
2020
Universidad de Salamanca
2020
Institut national de recherche en informatique et en automatique
2020
Learning to communicate in order share state information is an active problem the area of multi-agent reinforcement learning. The credit assignment problem, non-stationarity communication environment and encouraging agents be influenced by incoming messages are major challenges within this research field which need overcome learn a valid protocol. This paper introduces novel counterfactual learning (MACC) method adapts reasoning for communicating agents. Next, environment, while Q-function,...
In the upcoming decade and beyond, Cooperative, Connected Automated Mobility (CCAM) initiative will play a huge role in increasing road safety, traffic efficiency comfort of driving Europe. While several individual vehicular wireless communication technologies exist, there is still lack real flexible modular platforms that can support need for hybrid communication. this paper, we propose novel management framework (CAMINO), which incorporates both short-range direct long-range cellular...
The increase of Internet Things devices and the rise more computationally intense applications presents challenges for future architectures. We envision a in which edge, fog, cloud work together to execute applications. Because entire application cannot run on smaller edge or fog devices, we will need split into components. These components send event messages each other create single from multiple execution location can be optimized minimize resource consumption. In this paper, describe...
Recently, there has been an upsurge in the research on maritime vision, where a lot of works are influenced by application computer vision for Unmanned Surface Ve-hicles (USVs). Various sensor modalities such as camera, radar, and lidar have used to perform tasks object detection, segmentation, tracking, motion planning. A large subset this is focused video analysis, since most current vessel fleets con-tain camera's onboard various surveillance tasks. Due vast abundance data, scene change...
The notion of the Worst-Case Execution Time (WCET) allows system engineers to create safe real-time systems. This value is used schedule all software tasks before their deadlines. Failing these deadlines will cause catastrophic events, e.g. vehicle crashes, failing detect dangerous anomalies, etc. Different analysis methodologies exist determine WCET. However, methods do not provide early insight in WCET during development. Therefore, pessimistic assumptions are made by designers resulting...