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Full-Text Articles in Systems Science
Improved Pbs Algorithm For Multi-Agent Path Planning Based On Conflict Guidance And Punishment Mechanism, Jinbao Zhang, Jianlin Mao, Chengze Qian, Guimi Sun, Kaixin Tong
Improved Pbs Algorithm For Multi-Agent Path Planning Based On Conflict Guidance And Punishment Mechanism, Jinbao Zhang, Jianlin Mao, Chengze Qian, Guimi Sun, Kaixin Tong
Journal of System Simulation
Abstract: To address the bottleneck in which the priority-based search (priority-based search, PBS) algorithm for multi-agent path planning easily falls into conflict loops and generates invalid node expansions in complex scenarios, an improved algorithm based on conflict guidance and a punishment mechanism (improved PBS multi-agent path finding algorithm based on conflict guidance and punishment mechanism, CGP-PBS) was proposed. A conflict-guided node expansion mechanism was constructed; in high-level search, it comprehensively evaluated path cost and the number of conflicts, preferentially expanded child nodes with high potential for conflict resolution, and delayed the expansion of high-conflict nodes, thereby effectively compressing the search …
Multi-Scale Modeling Method For Intelligent Unmanned Aerial Vehicle Swarm Combat, Yelei Zhu, Shoulin Shen, Jiang Zhu, Chuanhua Wen
Multi-Scale Modeling Method For Intelligent Unmanned Aerial Vehicle Swarm Combat, Yelei Zhu, Shoulin Shen, Jiang Zhu, Chuanhua Wen
Journal of System Simulation
Abstract: Intelligent unmanned aerial vehicle swarm combat exhibits multi-scale characteristics of microlevel tactical autonomy, meso-level resource constraints, and macro-level network collaboration. In view of the problem that a single-scale modeling method is difficult to simultaneously characterize individual decision-making details, resource flow process, and system collaboration mechanism, a multi-scale modeling method integrating multi-agent modeling, system dynamics, and complex network theory was proposed. By designing six formal coupling operators to achieve cross-layer information mapping, a time progression mechanism based on a master-slave clock and hybrid synchronization was established, and a proof of error boundedness was provided. A prototype system was implemented on …
Llm-Driven Multi-Agent Social Network Simulation: Interdisciplinary Integration And Cutting-Edge Development, Jiting Li, Yi Sun, Yirong Wang, Yiqin Lin, Jun Jia, Gangsong Ding
Llm-Driven Multi-Agent Social Network Simulation: Interdisciplinary Integration And Cutting-Edge Development, Jiting Li, Yi Sun, Yirong Wang, Yiqin Lin, Jun Jia, Gangsong Ding
Journal of System Simulation
Abstract: The breakthrough of LLMs has provided powerful tools for social network research, advancing multi-agent social network simulation into a new era. This review systematically examined recent progress in LLM-driven multi-agent social network simulation research through a integrated perspective of multi-disciplines such as artificial intelligence, psychology, communication studies, and sociology. A three-tiered research system, which has gradually formed in this field and encompassed micro-level individual behaviors, meso-level interactive relations, and macro-level system emergence, was summarized. At the micro-level, research focuses on individual human behavior simulation, and numerous studies are dedicated to developing human-like agents with complex cognitive and affective architectures …
Survey Of Cooperative Multi-Agent Path Finding, Jun Xiong, Wenbo Zhang, Zhi Xiong, Feng Zhou, Bo Yang
Survey Of Cooperative Multi-Agent Path Finding, Jun Xiong, Wenbo Zhang, Zhi Xiong, Feng Zhou, Bo Yang
Journal of System Simulation
Abstract: Cooperative multi-agent path finding (Co-MAPF) has been widely applied in fields such as UAV formation and multi-agent systems, which enhances the overall system efficiency through task collaboration, path planning, and task execution among multiple agents. This paper introduced three main system architectures, namely centralized, distributed, and hybrid, along with their advantages and disadvantages based on the definition of the Co-MAPF problem, categorized, and reviewed mainstream Co-MAPF algorithms, including those based on sampling, search, intelligent optimization, and learning. Furthermore, this paper analyzed the main current challenges faced by Co-MAPF algorithms on the basis of summarizing existing research and outlined the …
Combat-Oriented Comprehensive Simulation And Verification Technology For Equipment System Rms, Yue Zhang, Wenliang Zhang, Qiang Feng, Xing Guo, Yi Ren, Zili Wang
Combat-Oriented Comprehensive Simulation And Verification Technology For Equipment System Rms, Yue Zhang, Wenliang Zhang, Qiang Feng, Xing Guo, Yi Ren, Zili Wang
Journal of System Simulation
Abstract:Existing reliability maintainability supportability (RMS) simulation and verification methods for equipment systems are typically conducted under standard conditions and suffer from weak combat environments and task modeling capabilities. To address this limitation, a multi-agent RMS simulation and verification framework was proposed. Key breakthroughs included agent modeling techniques for complex environments and variable tasks, interaction mechanisms among environmental agents, task agents, equipment, and support systems, and a simulation-based comprehensive RMS evaluation method. Case studies demonstrate that the proposed method effectively models complex environments and variable tasks, supports combat-oriented simulation and verification and design scheme evaluation, and meets combat-ready development requirements.
Real-Time Scheduling Method For Dynamic Flexible Job Shop Scheduling, Quan Jiang, Jingxuan Wei
Real-Time Scheduling Method For Dynamic Flexible Job Shop Scheduling, Quan Jiang, Jingxuan Wei
Journal of System Simulation
Abstract: A multi-objective dynamic flexible job shop scheduling problem model with machine breakdown and random jobs arrival is constructed to address the interference of dynamic events in manufacturing processing on the scheduling scheme, and a real-time scheduling method with multiobjective proximal policy optimization (MPPO) algorithm is proposed. The MPPO algorithm trains two agents, routing agent (RA) and sequencing agent (SA), for real-time scheduling and real-time processing of dynamic events. It employs a linear combination of weight vectors and reward vectors as reward signals and stores the agents' parameters for each weight vector to optimize multiple objectives. The required state information, …
Adaptive Pid Control Algorithm Based On Ppo, Zhiyong Zhou, Fei Mo, Kai Zhao, Yunbo Hao, Yufeng Qian
Adaptive Pid Control Algorithm Based On Ppo, Zhiyong Zhou, Fei Mo, Kai Zhao, Yunbo Hao, Yufeng Qian
Journal of System Simulation
Abstract: A six-axis robotic arm is built and simulated in a complex control environment with disturbances by using MATLAB physics engine and Python, which provides a trial-and-error environment for the robotic arm training that could not be provided in reality. Proximal policy optimization(PPO) algorithm in reinforcement learning is proposed to improve the traditional PID control algorithm. By introducing the multi-agent idea and on the basis of the different effects of the three parameters of PID on control system and the characteristics of the six-axis robotic arm, the three parameters are separately trained as different intelligent individuals to achieve a new …
Research And Development Of Simulation Training Platform For Multi-Agent Collaborative Decision-Making, Cheng Cheng, Zhijie Chen, Ziming Guo, Ni Li
Research And Development Of Simulation Training Platform For Multi-Agent Collaborative Decision-Making, Cheng Cheng, Zhijie Chen, Ziming Guo, Ni Li
Journal of System Simulation
Abstract: Reinforcement learning simulation platform can be an interactive and training environment for reinforcement learning. In order to make the simulation platform compatible with the multi-agent reinforcement learning algorithms and meet the needs of simulation in military field, the similar processes in multi-agent reinforcement learning algorithms are refined and a unified interface is designed to embed and verify different types of deep reinforcement learning algorithms on the simulation platform and to optimize the back-end service of the simulation platform to accelerate the training process of the algorithm model. The experimental results show that, by unifing the interface, the simulation platform …
Dynamic Simulation Of Urban Agglomeration Passenger Transport Network Vulnerability Based On Multi-Agent, Chengbing Li, Yunfei Li, Peng Wu
Dynamic Simulation Of Urban Agglomeration Passenger Transport Network Vulnerability Based On Multi-Agent, Chengbing Li, Yunfei Li, Peng Wu
Journal of System Simulation
Research on vulnerability of comprehensive passenger transportation network in urban agglomerations helps to ensure the transportation efficiency of intercity travel.A comprehensive passenger transport network model of urban agglomeration is built based on multi-layer complex network theory. Urban transportation transfer factors are considered, actual passenger flow is used to calibrate the station load and capacity and a dynamic model of network cascading failure is constructed. Multi-agents are used to simulate the actual passenger flow, Dijkstra algorithm is used to find the shortest path, and two time-dimensional vulnerability evaluation indicators are proposed.MATLAB is used to carry out the dynamic simulation …
Improved Social Force Model Based On Enhancing Psych Behavioral Heterogeneity, Yandong Liu, Gaoxiang Huang, Wen Chen
Improved Social Force Model Based On Enhancing Psych Behavioral Heterogeneity, Yandong Liu, Gaoxiang Huang, Wen Chen
Journal of System Simulation
Abstract: Simulating the evacuation behavior of people under anxiety is of great significance for solving the kinematic problems such as escape. At present, most at home and abroad studies consider the anxiety factors as the only medium of population evacuation without considering how external key factors affect anxiety factors in such emergency environments. The improved social force model is proposed, combined with Agent-based stampede risk assessment, the influence of key environmental variables on the anxiety factor is quantified. The psychological force parameters are introduced, and the impact of the anxiety factor on the actual evacuation process is applied to the …
Multiagent Following Multileader Algorithm Based On K-Means Clustering, Guodong Yuan, Ming He, Ziyu Ma, Weishi Zhang, Xueda Liu, Wei Li
Multiagent Following Multileader Algorithm Based On K-Means Clustering, Guodong Yuan, Ming He, Ziyu Ma, Weishi Zhang, Xueda Liu, Wei Li
Journal of System Simulation
Abstract: Three K-means clustering algorithms are proposed to prevent chaos in the formation of a multi-agent system (MAS) with multiple leaders. The algorithm divides the cluster into communities with the same number of leaders, and the agents within the community will follow the same leader. Among the three proposed algorithms, algorithm #1 is suitable for scenarios with widely distributed agents wherein rapid consensus can be achieved in the shortest time; algorithm #2 is suitable for scenarios with a sparse agent distribution and effectively prevented agent collisions; and algorithm #3 exhibits rapid convergence and considerably reduces the MAS control cost, …
Research On Opponent Modeling Framework For Multi-Agent Game Confrontation, Junren Luo, Wanpeng Zhang, Weilin Yuan, Zhenzhen Hu, Shaofei Chen, Jing Chen
Research On Opponent Modeling Framework For Multi-Agent Game Confrontation, Junren Luo, Wanpeng Zhang, Weilin Yuan, Zhenzhen Hu, Shaofei Chen, Jing Chen
Journal of System Simulation
Abstract: As the key technology of multi-agent game confrontation, opponent modeling is a typical cognitive modeling method of agent's behavior. Several typical models of multi-agent game confrontation,non-stationary problems, and meta-game theory are introduced; opponent modeling methods that concludes the frontier theory of opponent modeling are summarized, and the applications and challenges are analyzed. Based on the theory of meta-game, a general opponent modeling framework is constructed with three modules: opponent policy recognition and generation, opponent policy space reconstruction,and opponent exploitation. It is expected to provide theoretical and methodological reference for opponent modeling in multi-agent game confrontation.
Self-Learning-Based Multiple Spacecraft Evasion Decision Making Simulation Under Sparse Reward Condition, Zhao Yu, Jifeng Guo, Yan Peng, Chengchao Bai
Self-Learning-Based Multiple Spacecraft Evasion Decision Making Simulation Under Sparse Reward Condition, Zhao Yu, Jifeng Guo, Yan Peng, Chengchao Bai
Journal of System Simulation
Abstract: In order to improve the ability of spacecraft formation to evade multiple interceptors, aiming at the low success rate of traditional procedural maneuver evasion, a multi-agent cooperative autonomous decision-making algorithm, which is based on deep reinforcement learning method, is proposed. Based on the actor-critic architecture, a multi-agent reinforcement learning algorithm is designed, in which a weighted linear fitting method is proposed to solve the reliability allocation problem of the self-learning system. To solve the sparse reward problem in task scenario, a sparse reward reinforcement learning method based on inverse value method is proposed. According to the task scenario, …
Research Of Modeling Of Spatial Information Support Sos Based On Complex Network Theory, Qingjun Zhang, Mingzhi Zhang, Qingjuan Zhang, Wu Xi
Research Of Modeling Of Spatial Information Support Sos Based On Complex Network Theory, Qingjun Zhang, Mingzhi Zhang, Qingjuan Zhang, Wu Xi
Journal of System Simulation
Abstract: Spatial information support system as the main body of space operations, in the future network of joint operations, plays a central role. Based on the characteristics of spatial information support system, a modeling method combining multi-agent, multi-resolution and complex network was proposed, and the spatial information support system model framework was constructed. Multi-agent model, multi - resolution model and complex network model were established, and the connectivity rate in the complex network model was simulated and analyzed, so as to lay the foundation for further research on the modeling of spatial information support system.
System Dynamics And Multi-Agent Simulation Research On Ground Combatpersonnel Attrition, Xiaoxiong Hao, Jianwei Ma, Zhaohui Huang, Yungui Wang
System Dynamics And Multi-Agent Simulation Research On Ground Combatpersonnel Attrition, Xiaoxiong Hao, Jianwei Ma, Zhaohui Huang, Yungui Wang
Journal of System Simulation
Abstract: In order to study the law of the combat personnel attrition and guide the military medical logistics support, the relevant researches are systematically sorted out and the key questions are clarified. Based on Lanchester equation theory, a system dynamics model of the combat attrition process is established, and the consistency between the model conclusion and the historical experience is analyzed. A multi-agent model of the combat attrition process is also constructed, and the advantages and disadvantages of the two models are analyzed. The main conclusion is that the theoretical model’s outcomes of combat attrition are relatively consistent with the …
Research On Emergency Risk Decision Simulation Based On Multi-Agent And Prospect Theory, Wang Jian, Chenqi Situ, Shengqiang Yuan
Research On Emergency Risk Decision Simulation Based On Multi-Agent And Prospect Theory, Wang Jian, Chenqi Situ, Shengqiang Yuan
Journal of System Simulation
Abstract: Focusing on the modeling and the simulation of emergency response risk decision that multi-sections involve in, a simulation model and simulation framework based on multi-agent and prospect theory are proposed. By introducing agent theory, the multi-agent architecture model of emergency risk decision is described and the decision agent are modelled. By introducing prospect theory, following the dynamic evolution of emergencies, the impact of the psychological changes of the decision-makers have on the decision results is studied. The multi-agent emergency risk decision simulation framework is designed and implemented. Taking the risk decision of a fire emergency in the petrochemical plants …
Multi-Agent Modeling And Simulation On China's Marine Energy Channel Security, Yongchen Guo, Shen Yang
Multi-Agent Modeling And Simulation On China's Marine Energy Channel Security, Yongchen Guo, Shen Yang
Journal of System Simulation
Abstract: Security factors influencing China's offshore energy channel are analyzed, and the actual situation of China's oil import and transportation is described. Based on multi-agent modeling and simulation method, and starting at the micro level, the energy transport process is simulated and a multi-agent model of China's offshore energy channel (middle east lines) is built; and the simulation program on the NetLogo platform is conducted. The results show that the quantity of China’s VLCC is far from enough; the security impact of tropical cyclones is more serious than that of pirates; the increase proportion of carrier’s quantity is usually lower …
Dp-Q(Λ): Real-Time Path Planning For Multi-Agent In Large-Scale Web3d Scene, Fengting Yan, Jinyuan Jia
Dp-Q(Λ): Real-Time Path Planning For Multi-Agent In Large-Scale Web3d Scene, Fengting Yan, Jinyuan Jia
Journal of System Simulation
Abstract: The path planning of multi-agent in an unknown large-scale scene needs an efficient and stable algorithm, and needs to solve multi-agent collision avoidance problem, and then completes a real-time path planning in Web3D. To solve above problems, the DP-Q(λ) algorithm is proposed; and the direction constraints, high reward or punishment weight training methods are used to adjust the values of reward or punishment by using a probability p (0-1 random number). The value from reward or punishment determines its next step path planning strategy. If the next position is free, the agent could walk to it. The above strategy …