Imagen de Portada

Evolutionary Enhanced Multi-Agent Reinforcement Learning for Cooperative Air Combat

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Chengwei, Liu, Junlin, Gao, Yang
Formato:	Preprint
Publicado:	2026
Materias:	Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue
por: Lu, Wenhao, et al.
Publicado: (2025)

Coordinated Strategies in Realistic Air Combat by Hierarchical Multi-Agent Reinforcement Learning
por: Selmonaj, Ardian, et al.
Publicado: (2025)

Evolutionary Reinforcement Learning via Cooperative Coevolution
por: Hu, Chengpeng, et al.
Publicado: (2024)

Concept Learning for Cooperative Multi-Agent Reinforcement Learning
por: Ge, Zhonghan, et al.
Publicado: (2025)

Enhancing Aerial Combat Tactics through Hierarchical Multi-Agent Reinforcement Learning
por: Selmonaj, Ardian, et al.
Publicado: (2025)

Evo-MARL: Co-Evolutionary Multi-Agent Reinforcement Learning for Internalized Safety
por: Pan, Zhenyu, et al.
Publicado: (2025)

Enhancing Visual Grounding for GUI Agents via Self-Evolutionary Reinforcement Learning
por: Yuan, Xinbin, et al.
Publicado: (2025)

Quantum Multi-Agent Reinforcement Learning for Cooperative Mobile Access in Space-Air-Ground Integrated Networks
por: Kim, Gyu Seon, et al.
Publicado: (2024)

A Hierarchical Deep Reinforcement Learning Framework for 6-DOF UCAV Air-to-Air Combat
por: Chai, Jiajun, et al.
Publicado: (2022)

Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective
por: Liu, Qi, et al.
Publicado: (2024)

Cooperation and Fairness in Multi-Agent Reinforcement Learning
por: Aloor, Jasmine Jerry, et al.
Publicado: (2024)

Multi-level Advantage Credit Assignment for Cooperative Multi-Agent Reinforcement Learning
por: Zhao, Xutong, et al.
Publicado: (2025)

The Composite Task Challenge for Cooperative Multi-Agent Reinforcement Learning
por: Li, Yurui, et al.
Publicado: (2025)

Inferring Preferences from Demonstrations in Multi-objective Reinforcement Learning
por: Lu, Junlin, et al.
Publicado: (2024)

Empirical Study on Robustness and Resilience in Cooperative Multi-Agent Reinforcement Learning
por: Li, Simin, et al.
Publicado: (2025)

LERO: LLM-driven Evolutionary framework with Hybrid Rewards and Enhanced Observation for Multi-Agent Reinforcement Learning
por: Wei, Yuan, et al.
Publicado: (2025)

Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration
por: Kontogiannis, Andreas, et al.
Publicado: (2025)

Reaching Consensus in Cooperative Multi-Agent Reinforcement Learning with Goal Imagination
por: Wang, Liangzhou, et al.
Publicado: (2024)

Robust and Efficient Communication in Multi-Agent Reinforcement Learning
por: Liu, Zejiao, et al.
Publicado: (2025)

Explaining Strategic Decisions in Multi-Agent Reinforcement Learning for Aerial Combat Tactics
por: Selmonaj, Ardian, et al.
Publicado: (2025)

Demonstration Guided Multi-Objective Reinforcement Learning
por: Lu, Junlin, et al.
Publicado: (2024)

Multi-Agent Quantum Reinforcement Learning using Evolutionary Optimization
por: Kölle, Michael, et al.
Publicado: (2023)

Self-Clustering Hierarchical Multi-Agent Reinforcement Learning with Extensible Cooperation Graph
por: Fu, Qingxu, et al.
Publicado: (2024)

Tacit Learning with Adaptive Information Selection for Cooperative Multi-Agent Reinforcement Learning
por: Liu, Lunjun, et al.
Publicado: (2024)

VIKI-R: Coordinating Embodied Multi-Agent Cooperation via Reinforcement Learning
por: Kang, Li, et al.
Publicado: (2025)

Heterogeneous Multi-Agent Reinforcement Learning with Attention for Cooperative and Scalable Feature Transformation
por: Zhe, Tao, et al.
Publicado: (2025)

Combating Adversarial Attacks with Multi-Agent Debate
por: Chern, Steffi, et al.
Publicado: (2024)

Multi-Agent Collaborative Reward Design for Enhancing Reasoning in Reinforcement Learning
por: Yang, Pei, et al.
Publicado: (2025)

MASH: Cooperative-Heterogeneous Multi-Agent Reinforcement Learning for Single Humanoid Robot Locomotion
por: Liu, Qi, et al.
Publicado: (2025)

Communication Gain and Delay Cost Under Cross-Timestep Delays in Cooperative Multi-Agent Reinforcement Learning
por: Gao, Zihong, et al.
Publicado: (2026)

CCL: Collaborative Curriculum Learning for Sparse-Reward Multi-Agent Reinforcement Learning via Co-evolutionary Task Evolution
por: Lin, Yufei, et al.
Publicado: (2025)

GUI-Shift: Enhancing VLM-Based GUI Agents through Self-supervised Reinforcement Learning
por: Gao, Longxi, et al.
Publicado: (2025)

LAMARL: LLM-Aided Multi-Agent Reinforcement Learning for Cooperative Policy Generation
por: Zhu, Guobin, et al.
Publicado: (2025)

A Meta-Learning Approach for Multi-Objective Reinforcement Learning in Sustainable Home Environments
por: Lu, Junlin, et al.
Publicado: (2024)

DRAFT-RL: Multi-Agent Chain-of-Draft Reasoning for Reinforcement Learning-Enhanced LLMs
por: Li, Yuanhao, et al.
Publicado: (2025)

A Spatiotemporal Stealthy Backdoor Attack against Cooperative Multi-Agent Deep Reinforcement Learning
por: Yu, Yinbo, et al.
Publicado: (2024)

Coordination Matters: Evaluation of Cooperative Multi-Agent Reinforcement Learning
por: Cardei, Maria Ana, et al.
Publicado: (2026)

LLM-Guided Communication for Cooperative Multi-Agent Reinforcement Learning
por: Bae, Sangjun, et al.
Publicado: (2026)

Multi-Agent Reinforcement Learning with Communication-Constrained Priors
por: Yang, Guang, et al.
Publicado: (2025)

MO-MIX: Multi-Objective Multi-Agent Cooperative Decision-Making With Deep Reinforcement Learning
por: Hu, Tianmeng, et al.
Publicado: (2026)