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path scheduling » task scheduling (Expand Search)
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path scheduling » task scheduling (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
agent » agents (Expand Search)
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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A Graph Heuristic Approach for the Data Path Allocation Problem
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masterThesis -
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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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Multi-Robot Map Exploration Based on Multiple Rapidly-Exploring Randomized Trees
Published 2017Get full text
doctoralThesis -
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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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An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
Published 2020Get full text
doctoralThesis -
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Activity-level space scheduling
Published 1992“…An interactive and graphical decision-support tool, named MovePlan, is presented to assist in space scheduling. Its output layouts can be used to refine individual robot's trajectories using traditional path-planning algorithms.…”
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Loop based scheduling for high level synthesis
Published 1995“…This paper describes a new loop based scheduling algorithm. The algorithm aims at reducing the runtime processing complexity of path based scheduling techniques. …”
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Deep Reinforcement Learning for Resource Constrained HLS Scheduling
Published 2022“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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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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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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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. …”