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learning algorithm » learning algorithms (Expand Search)
fluent learning » student learning (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
agents based » agent based (Expand Search), event based (Expand Search)
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm
Published 2023Subjects: Get full text
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Agent-Based Reactive Geographic Routing Protocol for Internet of Vehicles
Published 2023“…In this paper, we first propose a novel lightweight location service that permits to discover all the geographical paths between two vehicles based on smart mobile agents. Second, we proposed ARGENT an Agent-Based Reactive Geographic Routing Protocol that couples the routing process with the novel lightweight location service. …”
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Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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ARDENT: A Proactive Agent-Based Routing Protocol for Internet of Vehicles
Published 2023“…Then, we present an Agent-Based Proactive Geographic Routing Protocol called ARDENT to route data packets with reduced delay and higher delivery ratio. …”
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Distributed optimal coverage control in multi-agent systems: Known and unknown environments
Published 2024“…<p>This paper introduces a novel approach to solve the coverage optimization problem in multi-agent systems. The proposed technique offers an optimal solution with a lower cost with respect to conventional Voronoi-based techniques by effectively handling the issue of agents remaining stationary in regions void of information using a ranking function. …”
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Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization
Published 2023“…This paper presents a reinforcement learning agent-based model that works by incorporating the MESA environment with the Stone Soup radar systems simulator. …”
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Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees
Published 2017Get full text
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…UniBFS exploits the inherent characteristic of binary algorithms-binary coding-to search the entire problem space for identifying relevant features while avoiding irrelevant ones. …”
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Auto-indexing Arabic texts based on association rule data mining. (c2015)
Published 2015“…Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
Published 2020Get full text
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A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security
Published 2023“…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
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Single channel speech denoising by DDPG reinforcement learning agent
Published 2025“…In this paper, a novel SD algorithm is presented based on the deep deterministic policy gradient (DDPG) agent; an off-policy reinforcement learning (RL) agent with a continuous action space. …”
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Information reconciliation through agent controlled graph model. (c2018)
Published 2018“…Our approach provides a damage assessment and recovery algorithm that is based on agents and graphs.…”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
Published 2025“…Given the complexity of the LDTP solution for managing online requests, we propose a real-time, lightweight solution using multi-agent meta-reinforcement learning. Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. …”
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Social spider optimization algorithm: survey and new applications
Published 2024“…Each spider has a weight based on the value of fitness. This algorithm consists of two search spiders called agents: males and females. …”
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