Showing 101 - 120 results of 1,487 for search 'agent’s state', query time: 0.06s Refine Results
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    Dynamic rationing using agent-based modeling of the assembly process of equipment for nuclear power plants by I. A. Loskutov, D. A. Skvortsova, V. G. Iskandarova

    Published 2023-02-01
    “…The accuracy of calculations of data convergence, income on the environment in Matlab Mathworks and Microsoft Excel during manual modeling is argued. The agreements state a slight deviation from the data model of the developed agent-based model of a practical experiment carried out as part of the implementation of the contract for the creation of equipment for a new power unit, a causal analysis is carried out. …”
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  6. 106

    Observer-Based Aperiodic Time-Triggered Intermittent Control for Exponential Consensus of Multi-Agent Systems by Xueming Xu, Qingzhi Wang, Baozeng Fu, Lijie Wang

    Published 2025-01-01
    “…OATICP only relies on the output information at sampling instants to estimate the state of the agent itself, and the state estimation information of the neighbor agents at sampling instants to generate the control signal. …”
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    Task Offloading with LLM-Enhanced Multi-Agent Reinforcement Learning in UAV-Assisted Edge Computing by Feifan Zhu, Fei Huang, Yantao Yu, Guojin Liu, Tiancong Huang

    Published 2024-12-01
    “…Overall, this framework significantly advances UAV trajectory optimization and enhances the performance of multi-agent systems within UAV-assisted edge computing environments.…”
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    Pri-DDQN: learning adaptive traffic signal control strategy through a hybrid agent by Yanliu Zheng, Juan Luo, Han Gao, Yi Zhou, Keqin Li

    Published 2024-11-01
    “…With the goal of minimizing the waiting time and queue length at intersections, we use double DQN to train the agent, incorporate traffic state and reward into the loss function, and update the target network parameters asynchronously, to improve the agent’s learning ability. …”
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    Optimal Skipping Rates: Training Agents with Fine-Grained Control Using Deep Reinforcement Learning by Adil Khan, Jiang Feng, Shaohui Liu, Muhammad Zubair Asghar

    Published 2019-01-01
    “…The agent is trained and tested on Doom’s basic scenario(s) where the results are compared and found to be 10% better compared to the existing state-of-the-art research work on Doom-based agents. …”
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    Enhancing Channel Selection in 5G with Decentralized Federated Multi-Agent Deep Reinforcement Learning by Taghi Shahgholi, Keyhan Khamforoosh, Amir Sheikhahmadi, Sadoon Azizi

    Published 2024-12-01
    “…The DRL-based decision-making model considers crucial factors, such as instantaneous channel state information and historical link selections, to dynamically allocate channels and transmission power, leading to improved system efficiency.By incorporating federated learning, we enable knowledge sharing and synchronization among the decentralized vehicular agents. …”
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    “They paved the Atlantic with books”: William and Jenny Bradley, literary agents and cultural passeurs across borders by Laurence Cossu-Beaumont

    Published 2023-06-01
    “…This article first aims at including the two agents into the communications circuit relevant to book history that unfolds from writer to editor and on to reader, at a time when the book industry became more international. …”
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