Suchergebnisse - "multi-agent deep deterministic policy gradient algorithm"
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Multi-agent deep deterministic policy gradient algorithm for peer-to-peer energy trading considering distribution network constraints
ISSN: 0306-2619, 1872-9118Veröffentlicht: Elsevier Ltd 01.07.2022Veröffentlicht in Applied energy (01.07.2022)“… To address the challenge, we first formulate the above problem as a Markov decision process and propose a multi-agent deep deterministic policy gradient algorithm to learn optimal energy trading decisions …”
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Simulation optimization of highway hard shoulder running based on multi-agent deep deterministic policy gradient algorithm
ISSN: 1110-0168Veröffentlicht: Elsevier B.V 01.04.2025Veröffentlicht in Alexandria engineering journal (01.04.2025)“… To alleviate traffic congestion and reduce vehicle emissions, the use of hard shoulder running (HSR) has emerged as a sustainable and cost-effective active …”
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Research on the influence of multi-agent deep deterministic policy gradient algorithm key parameters in typical scenarios
ISSN: 1742-6588, 1742-6596Veröffentlicht: Bristol IOP Publishing 01.10.2024Veröffentlicht in Journal of physics. Conference series (01.10.2024)“… The MADDPG algorithm is widely used and relatively complete, but there is no intuitive data support for the values of some key parameters. Therefore, the …”
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Robust Adaptive Fractional-Order PID Controller Design for High-Power DC-DC Dual Active Bridge Converter Enhanced Using Multi-Agent Deep Deterministic Policy Gradient Algorithm for Electric Vehicles
ISSN: 1996-1073, 1996-1073Veröffentlicht: Basel MDPI AG 01.06.2025Veröffentlicht in Energies (Basel) (01.06.2025)“… The Dual Active Bridge converter (DABC), known for its bidirectional power transfer capability and high efficiency, plays a crucial role in various …”
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A multi-agent deep deterministic policy gradient algorithm integrated with the A algorithm for multiple-equipment integrated scheduling in automated container terminals
ISSN: 0305-215X, 1029-0273Veröffentlicht: 29.08.2025Veröffentlicht in Engineering optimization (29.08.2025)Volltext
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Optimal operation of regional integrated energy system based on multi-agent deep deterministic policy gradient algorithm
ISSN: 2352-4847, 2352-4847Veröffentlicht: Elsevier Ltd 01.11.2022Veröffentlicht in Energy reports (01.11.2022)“… Therefore, an optimal operation method based on the multi-agent deep deterministic policy gradient algorithm (MADDPG) is proposed …”
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Fire Evacuation Path Planning Based on Improved MADDPG (Multi-Agent Deep Deterministic Policy Gradient) Algorithm
ISSN: 2158-107X, 2156-5570Veröffentlicht: West Yorkshire Science and Information (SAI) Organization Limited 2024Veröffentlicht in International journal of advanced computer science & applications (2024)“… The lack of a scientific and reasonable optimal evacuation path planning scheme is one of the main causes of casualties in fire accidents. In addition to the …”
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Multi-Microgrid Energy Trading Strategy Based on Multi-Agent Deep Deterministic Policy Gradient Algorithm
ISSN: 2444-8656, 2444-8656Veröffentlicht: Beirut Sciendo 01.01.2024Veröffentlicht in Applied mathematics and nonlinear sciences (01.01.2024)“… Compared to individual microgrid, multi-microgrid (MMG) system can enhance the overall utilization of renewable energy, effectively improve the operational …”
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A Pursuit Strategy for Multi-Agent Pursuit-Evasion Game via Multi-Agent Deep Deterministic Policy Gradient Algorithm
ISSN: 2771-7372Veröffentlicht: IEEE 28.10.2022Veröffentlicht in Proceedings of ... IEEE International Conference on Unmanned Systems (Online) (28.10.2022)“… This paper studies a classical pursuit-evasion problem. The pursuer attempts to capture the faster evader in a bounded area. The velocity of evader is 1.2 …”
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Grid-area coordinated load frequency control strategy using large-scale multi-agent deep reinforcement learning
ISSN: 2352-4847, 2352-4847Veröffentlicht: Elsevier Ltd 01.11.2022Veröffentlicht in Energy reports (01.11.2022)“… In order to enable full participation of high-performance units controlled by different dispatching centers in the performance-based frequency regulation …”
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Improved Multi-Agent Deep Deterministic Policy Gradient for Path Planning-Based Crowd Simulation
ISSN: 2169-3536, 2169-3536Veröffentlicht: Piscataway IEEE 2019Veröffentlicht in IEEE access (2019)“… Deep reinforcement learning (DRL) has been proved to be more suitable than reinforcement learning for path planning in large-scale scenarios. In order to more …”
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基于多智能体深度强化学习的无人艇集群博弈对抗研究
ISSN: 2096-3920Veröffentlicht: 大连海事大学船舶与海洋工程学院,辽宁大连, 116026 01.02.2024Veröffentlicht in 水下无人系统学报 (01.02.2024)“… TJ630%U664.82; 基于未来现代化海上作战背景,提出了利用多智能体深度强化学习方案来完成无人艇群博弈对抗中的协同围捕任务.首先,根据不同的作战模式和应用场景,提出基于分 …”
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Research on Game Confrontation of Unmanned Surface Vehicles Swarm Based on Multi-Agent Deep Reinforcement Learning
ISSN: 2096-3920Veröffentlicht: Science Press (China) 01.02.2024Veröffentlicht in 水下无人系统学报 (01.02.2024)“… of unmanned surface vehicles (USVs). First, based on different combat modes and application scenarios, a multi-agent deep deterministic policy gradient algorithm based on distributed execution was determined, and its principle was introduced …”
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Multi-Agent Deep Deterministic Policy Gradient Algorithm Based on Classification Experience Replay
ISSN: 2689-6621Veröffentlicht: IEEE 03.10.2022Veröffentlicht in IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) (Online) (03.10.2022)“… In recent years, multi-agent reinforcement learning has been applied in many fields, such as urban traffic control, autonomous UAV operations, etc. Although …”
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Research on Bidding Strategy of Thermal Power Companies in Electricity Market Based on Multi-Agent Deep Deterministic Policy Gradient
ISSN: 2169-3536, 2169-3536Veröffentlicht: Piscataway IEEE 2021Veröffentlicht in IEEE access (2021)“… With the continuous improvement of new energy penetration in the power system, the price of the spot market of power frequently fluctuates greatly, which …”
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Large-scale deep reinforcement learning method for energy management of power supply units considering regulation mileage payment
ISSN: 2296-598X, 2296-598XVeröffentlicht: Frontiers Media S.A 14.03.2024Veröffentlicht in Frontiers in energy research (14.03.2024)“… To improve automatic generation control (AGC) performance and reduce the wastage of regulation resources in interconnected grids including high-proportion …”
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A multi-agent deep reinforcement learning-based “Octopus” cooperative load frequency control for an interconnected grid with various renewable units
ISSN: 2213-1388Veröffentlicht: Elsevier Ltd 01.06.2022Veröffentlicht in Sustainable energy technologies and assessments (01.06.2022)“… •A data-driven “octopus” cooperative load frequency control (OC-LFC) method for an interconnected power system is proposed.•An TED-MADDPG algorithm is proposed …”
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Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraints
ISSN: 2331-8422Veröffentlicht: Ithaca Cornell University Library, arXiv.org 20.08.2021Veröffentlicht in arXiv.org (20.08.2021)“… To address the challenge, we first formulate the above problem as a Markov decision process and propose a multi-agent deep deterministic policy gradient algorithm to learn optimal energy trading decisions …”
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AUV Swarm Confrontation Search Method Based on the MADDPG Algorithm
ISSN: 1948-9447Veröffentlicht: IEEE 16.05.2025Veröffentlicht in Chinese Control and Decision Conference (16.05.2025)“… In this paper, an Autonomous Underwater Vehicle (AUV) swarm confrontation search method based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) …”
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Bidding Strategy for Thermal Power Generation Companies Based on Multi-agent Deep Deterministic Policy Gradient Algorithm
ISSN: 1004-9649Veröffentlicht: State Grid Energy Research Institute 01.11.2024Veröffentlicht in Zhongguo dian li (01.11.2024)“… A bidding strategy model is constructed based on the multi-agent deep deterministic policy gradient algorithm to analyze the differential bidding strategies for different combinations of thermal …”
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