Search Results - "Bentahar, Jamal"

Formal verification of group and propagated trust in multi-agent systems by Drawel, Nagat, Bentahar, Jamal, Laarej, Amine, Rjoub, Gaith

“…While modeling trust in multi-agent systems provides a fundamental basis for promoting safe interactions and imitating agents reasoning mechanisms, exploiting…”
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Detonation cell size prediction based on artificial neural networks with chemical kinetics and thermodynamic parameters by Bakalis, Georgios, Valipour, Maryam, Bentahar, Jamal, Kadem, Lyes, Teng, Honghui, Ng, Hoi Dick

“…In this paper, we develop a series of Artificial Neural Networks (ANN) using different chemical kinetic and thermodynamic input parameters to predict…”
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BigTrustScheduling: Trust-aware big data task scheduling approach in cloud computing environments by Rjoub, Gaith, Bentahar, Jamal, Wahab, Omar Abdel

“…Big data task scheduling in cloud computing environments has gained considerable attention in the past few years, due to the exponential growth in the number…”
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Federated against the cold: A trust-based federated learning approach to counter the cold start problem in recommendation systems by Wahab, Omar Abdel, Rjoub, Gaith, Bentahar, Jamal, Cohen, Robin

“…•Federated learning-based recommendation system for cold-start items.•Trust establishment for recommenders that considers resource utilization and…”
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Combining Knowledge Graph and Word Embeddings for Spherical Topic Modeling by Ennajari, Hafsa, Bouguila, Nizar, Bentahar, Jamal

“…Probabilistic topic models are considered as an effective framework for text analysis that uncovers the main topics in an unlabeled set of documents. However,…”
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Trust-driven reinforcement selection strategy for federated learning on IoT devices by Rjoub, Gaith, Wahab, Omar Abdel, Bentahar, Jamal, Bataineh, Ahmed

“…Federated learning is a distributed machine learning approach that enables a large number of edge/end devices to perform on-device training for a single…”
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Target localization using Multi-Agent Deep Reinforcement Learning with Proximal Policy Optimization by Alagha, Ahmed, Singh, Shakti, Mizouni, Rabeb, Bentahar, Jamal, Otrok, Hadi

“…Target localization refers to identifying a target location based on sensory data readings gathered by sensing agents (robots, UAVs), surveying a certain area…”
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Graph convolutional recurrent networks for reward shaping in reinforcement learning by Sami, Hani, Bentahar, Jamal, Mourad, Azzam, Otrok, Hadi, Damiani, Ernesto

“…In this paper, we consider the problem of low-speed convergence in Reinforcement Learning (RL). As a solution, various potential-based reward shaping…”
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Demand-Driven Deep Reinforcement Learning for Scalable Fog and Service Placement by Sami, Hani, Mourad, Azzam, Otrok, Hadi, Bentahar, Jamal

“…The increasing number of Internet of Things (IoT) devices necessitates the need for a more substantial fog computing infrastructure to support the users'…”
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A comprehensive survey on applications of transformers for deep learning tasks by Islam, Saidul, Elmekki, Hanae, Elsebai, Ahmed, Bentahar, Jamal, Drawel, Nagat, Rjoub, Gaith, Pedrycz, Witold

“…Transformers are Deep Neural Networks (DNN) that utilize a self-attention mechanism to capture contextual relationships within sequential data. Unlike…”
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A Crowd-Sensing Framework for Allocation of Time-Constrained and Location-Based Tasks by Estrada, Rebeca, Mizouni, Rabeb, Otrok, Hadi, Ouali, Anis, Bentahar, Jamal

“…Thanks to the capabilities of the built-in sensors of smart devices, mobile crowd-sensing (MCS) has become a promising technique for massive data collection…”
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AI-Based Resource Provisioning of IoE Services in 6G: A Deep Reinforcement Learning Approach by Sami, Hani, Otrok, Hadi, Bentahar, Jamal, Mourad, Azzam

“…Currently, researchers have motivated a vision of 6G for empowering the new generation of the Internet of Everything (IoE) services that are not supported by…”
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Data sources and approaches for building occupancy profiles at the urban scale – A review by Nejadshamsi, Shayan, Eicker, Ursula, Wang, Chun, Bentahar, Jamal

“…Buildings’ occupant profiles at the urban scale play an important role in various applications like Urban Building Energy Modeling (UBEM) and assessing energy…”
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Multi-dimensional trust for context-aware services computing by Mousa, Afaf, Bentahar, Jamal, Alam, Omar

“…•We introduce a novel trust model of IoT services considering dynamic environments.•We define a subjective, objective, collusion resistant and bootstrapped…”
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A geographic-semantic context-aware urban commuting flow prediction model using graph neural network by Nejadshamsi, Shayan, Bentahar, Jamal, Eicker, Ursula, Wang, Chun, Jamshidi, Faezeh

“…Urban commuting flow prediction is crucial for urban planning, transportation optimization, and supply chain management. Traditional models and machine…”
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A reinforcement learning model for the reliability of blockchain oracles by Taghavi, Mona, Bentahar, Jamal, Otrok, Hadi, Bakhtiyari, Kaveh

“…Smart contracts struggle with the major limitation of operating on data that is solely residing on the blockchain network. The need of recruiting third…”
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A survey on trust and reputation models for Web services: Single, composite, and communities by Wahab, Omar Abdel, Bentahar, Jamal, Otrok, Hadi, Mourad, Azzam

“…Web service selection constitutes nowadays a major challenge that is still attracting the research community to work on and investigate. The problem arises…”
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MV-Checker: A software tool for multi-valued model checking intelligent applications with trust and commitment by Alwhishi, Ghalya, Bentahar, Jamal, Elwhishi, Ahmed, Pedrycz, Witold

“…Intelligent applications are highly susceptible to uncertainty and inconsistency due to the intense and intricate interactions among their autonomous…”
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Blockchain-based crowdsourced deep reinforcement learning as a service by Alagha, Ahmed, Otrok, Hadi, Singh, Shakti, Mizouni, Rabeb, Bentahar, Jamal

“…Deep Reinforcement Learning (DRL) has emerged as a powerful paradigm for solving complex problems. However, its full potential remains inaccessible to a…”
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Model checking combined trust and commitments in Multi-Agent Systems by Baharloo, Narges, Bentahar, Jamal, Drawel, Nagat, Pedrycz, Witold

“…Trust and social commitments have been studied with different objectives for communication in Multi-Agent Systems (MASs) separately. The purpose of this paper…”
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