Search Results - greedy action-based distributed task allocation algorithm~

POMCP-based decentralized spatial task allocation algorithms for partially observable environments.

Authors: Amini, Sara Palhang, Maziar Mozayani, Nasser

Source: Applied Intelligence; May2023, Vol. 53 Issue 10, p12613-12631, 19p

Subject Terms: ALGORITHMS, DISTRIBUTED algorithms

Centralized and Distributed Task Allocation in Multi-Robot Teams via a Stochastic Clustering Auction.

Authors: Zhang, Kai Collins, Emmanuel G. Shi, Dongqing

Source: ACM Transactions on Autonomous & Adaptive Systems; 2012, Vol. 7 Issue 2, p21-21:22, 22p

Subject Terms: ASSIGNMENT problems (Programming), ROBOTS, ALGORITHMS, STOCHASTIC analysis, MAXIMA & minima, MARKOV processes, PERFORMANCE evaluation, EXPERIMENTS

TASK ALLOCATION ALGORITHM BASED ON IMMUNE SYSTEM FOR AUTONOMOUSLY COOPERATIVE MULTI-ROBOT SYSTEM.

Authors: Yunyuan Gao

Source: Intelligent Automation & Soft Computing; Jun2009, Vol. 15 Issue 2, p263-273, 11p, 3 Diagrams, 2 Charts, 3 Graphs

Subject Terms: AUTONOMOUS robots, ROBOT control systems, SIMULATION methods & models, AUTOMATIC control systems, GENETIC algorithms, IMMUNE system

USVs Path Planning for Maritime Search and Rescue Based on POS-DQN: Probability of Success-Deep Q-Network.

Authors: Liu, Lu Shan, Qihe Xu, Qi

Source: Journal of Marine Science & Engineering; Jul2024, Vol. 12 Issue 7, p1158, 19p

Subject Terms: DEEP reinforcement learning, RESCUE work, AUTONOMOUS vehicles, PROBLEM solving, ALGORITHMS

QoS-driven reinforcement learning-based resource allocation in space–air–ground–sea integrated networks.

Authors: Tang, Bing Li, Jiayao Cao, Yujun et al.

Source: Cluster Computing; 2025, Vol. 28 Issue 8, p1-17, 17p

Research on Task Allocation in Four-Way Shuttle Storage and Retrieval Systems Based on Deep Reinforcement Learning.

Authors: Zhang, Zhongwei Wang, Jingrui Jin, Jie et al.

Source: Sustainability (2071-1050); Aug2025, Vol. 17 Issue 15, p6772, 33p

A Deep Reinforcement Learning-Driven Seagull Optimization Algorithm for Solving Multi-UAV Task Allocation Problem in Plateau Ecological Restoration.

Authors: Qin, Lijing Zhou, Zhao Liu, Huan et al.

Source: Drones (2504-446X); Jun2025, Vol. 9 Issue 6, p436, 19p

Dynamic obstacle avoidance scheduling strategy for AGVs in dual-layer production lines considering task completion time and energy consumption.

Authors: Chen, Yiqiao Chen, Haiduo Chen, Shimiao et al.

Source: Production Engineering (09446524); Dec2025, Vol. 19 Issue 6, p1139-1162, 24p

Speeding Task Allocation Search for Reconfigurations in Adaptive Distributed Embedded Systems Using Deep Reinforcement Learning.

Authors: Rotaeche, Ramón Ballesteros, Alberto Proenza, Julián

Source: Sensors (14248220); Jan2023, Vol. 23 Issue 1, p548, 23p

Subject Terms: POLYNOMIAL time algorithms, REINFORCEMENT learning, COMBINATORIAL optimization, TIME management

A Review of Task Allocation Methods for UAVs.

Authors: Skaltsis, George Marios Shin, Hyo-Sang Tsourdos, Antonios

Source: Journal of Intelligent & Robotic Systems; Dec2023, Vol. 109 Issue 4, p1-24, 24p

A Hierarchical Reinforcement Learning Framework for Multi-Agent Cooperative Maneuver Interception in Dynamic Environments.

Authors: Huang, Qinlong Luo, Yasong Liu, Zhong et al.

Source: Journal of Marine Science & Engineering; Jul2025, Vol. 13 Issue 7, p1271, 32p

Subject Terms: REINFORCEMENT learning, GRAPH neural networks, MULTIAGENT systems, RESOURCE management, DEEP learning, ROBOTIC path planning

Joint Power Allocation Algorithm Based on Multi-Agent DQN in Cognitive Satellite–Terrestrial Mixed 6G Networks.

Authors: Zhai, Yifan Ma, Zhongjun He, Bo et al.

Source: Mathematics (2227-7390); Oct2025, Vol. 13 Issue 19, p3133, 17p

Subject Terms: 6G networks, REINFORCEMENT learning, COMPARATIVE studies, INTELLIGENT agents, POWER resources management, NETWORK performance, TELECOMMUNICATION systems, INTERFERENCE suppression

Fog Computing Tasks Management Based on Federated Reinforcement Learning.

Authors: Azarkasb, Seyed Omid Khasteh, Seyed Hossein

Source: Journal of Grid Computing; Mar2025, Vol. 23 Issue 1, p1-46, 46p

Multi-User Computation Offloading and Resource Allocation Algorithm in a Vehicular Edge Network.

Authors: Liu, Xiangyan Zheng, Jianhong Zhang, Meng et al.

Source: Sensors (14248220); Apr2024, Vol. 24 Issue 7, p2205, 19p

Subject Terms: REINFORCEMENT learning, RESOURCE allocation, MACHINE learning, DEEP reinforcement learning, EDGE computing, NONLINEAR programming, ALGORITHMS

Spectrum-efficient user grouping and resource allocation based on deep reinforcement learning for mmWave massive MIMO-NOMA systems.

Authors: Wang, Minghao Liu, Xin Wang, Fang et al.

Source: Scientific Reports; 4/17/2024, Vol. 14 Issue 1, p1-18, 18p

Subject Terms: DEEP reinforcement learning, REINFORCEMENT learning, MULTIPLE access protocols (Computer network protocols), RESOURCE allocation, GREEDY algorithms, INTERFERENCE suppression

Development of a Fleet Management System for Multiple Robots' Task Allocation Using Deep Reinforcement Learning.

Authors: Dai, Yanyan Kim, Deokgyu Lee, Kidong

Source: Processes; Dec2024, Vol. 12 Issue 12, p2921, 15p

Subject Terms: DEEP reinforcement learning, LEARNING management system, ROBOT control systems, COST control, ROBOTICS

Task Scheduling Mechanism Based on Reinforcement Learning in Cloud Computing.

Authors: Wang, Yugui Dong, Shizhong Fan, Weibei

Source: Mathematics (2227-7390); Aug2023, Vol. 11 Issue 15, p3364, 17p

Subject Terms: CLOUD computing, REINFORCEMENT learning, VIRTUAL machine systems, PARTICLE swarm optimization, SCHEDULING, RESOURCE allocation

Multi-robot task allocation in e-commerce RMFS based on deep reinforcement learning.

Authors: Ruiping Yuan Jiangtao Dou Juntao Li et al.

Source: Mathematical Biosciences & Engineering; 2023, Vol. 20 Issue 2, p1903-1918, 16p, 4 Diagrams, 1 Chart, 4 Graphs

Efficient and Energy-Saving Computation Offloading Mechanism with Energy Harvesting for IoT.

Authors: Zhang, Yawen Miao, Yifeng Pan, Shujia et al.

Source: Security & Communication Networks; 12/27/2021, p1-10, 10p

Subject Terms: ENERGY harvesting, MOBILE computing, INTERNET of things, GREEDY algorithms, COMPUTER systems, DEEP learning, TIME management

A Resource Allocation Algorithm for Cloud-Network Collaborative Satellite Networks with Differentiated QoS Requirements.

Authors: Shao, Zhimin Ding, Qingyang Meng, Lingzhen et al.

Source: Electronics (2079-9292); Oct2024, Vol. 13 Issue 19, p3843, 19p

Subject Terms: TELECOMMUNICATION satellites, REINFORCEMENT learning, TELECOMMUNICATION, RESOURCE allocation, QUALITY of service, VIRTUAL networks