141 citations · 293 across the 10 of their papers we have counts for
10 papers
Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning
Ahmed Alagha, Jamal Bentahar, Hadi Otrok +2
Multi-Agent Deep Reinforcement Learning (MDRL) is a promising research area in which agents learn complex behaviors in cooperative or competitive environments. However, MDRL comes…
Enhancing IoT Intelligence: A Transformer-based Reinforcement Learning Methodology
Gaith Rjoub, Saidul Islam, Jamal Bentahar +2
The proliferation of the Internet of Things (IoT) has led to an explosion of data generated by interconnected devices, presenting both opportunities and challenges for intelligent…
A Comprehensive Survey on Applications of Transformers for Deep Learning Tasks
Saidul Islam, Hanae Elmekki, Ahmed Elsebai +4
Transformer is a deep neural network that employs a self-attention mechanism to comprehend the contextual relationships within sequential data. Unlike conventional neural networks…
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions
Hani Sami, Ahmad Hammoud, Mouhamad Arafeh +14
The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual…
A Survey on Explainable Artificial Intelligence for Cybersecurity
Gaith Rjoub, Jamal Bentahar, Omar Abdel Wahab +5
The black-box nature of artificial intelligence (AI) models has been the source of many concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) i…
ON-DEMAND-FL: A Dynamic and Efficient Multi-Criteria Federated Learning Client Deployment Scheme
Mario Chahoud, Hani Sami, Azzam Mourad +4
In this paper, we increase the availability and integration of devices in the learning process to enhance the convergence of federated learning (FL) models. To address the issue of…
Reward Shaping Using Convolutional Neural Network
Hani Sami, Hadi Otrok, Jamal Bentahar +2
In this paper, we propose Value Iteration Network for Reward Shaping (VIN-RS), a potential-based reward shaping mechanism using Convolutional Neural Network (CNN). The proposed VIN…
Reinforcement Learning Framework for Server Placement and Workload Allocation in Multi-Access Edge Computing
Anahita Mazloomi, Hani Sami, Jamal Bentahar +2
Cloud computing is a reliable solution to provide distributed computation power. However, real-time response is still challenging regarding the enormous amount of data generated by…
Cloud computing as a platform for monetizing data services: A two-sided game business model
Ahmed Saleh Bataineh, Jamal Bentahar, Rabeb Mizouni +3
With the unprecedented reliance on cloud computing as the backbone for storing today's big data, we argue in this paper that the role of the cloud should be reshaped from being a p…
A two-level solution to fight against dishonest opinions in recommendation-based trust systems
Omar Abdel Wahab, Jamal Bentahar, Robin Cohen +2
In this paper, we propose a mechanism to deal with dishonest opinions in recommendation-based trust models, at both the collection and processing levels. We consider a scenario in…