Multi-agent modeling and simulation in the AI age

Reinforcement Learning: An Introduction

Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225 · see citing works

Reinforcement Learning: An Introduction

Sutton, R. S., & Barto, A. (2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 25,263 · see citing works

Playing Atari with Deep Reinforcement Learning

Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., & Riedmiller, M. (2013) · arXiv · doi:10.48550/arxiv.1312.5602 · Cited by 9,471 · see citing works

Untitled work

(2000) · University of Maribor digital library (University of Maribor) · Cited by 9,354 · see citing works

Untitled work

(1999) · Cited by 5,147 · see citing works

Grandmaster level in StarCraft II using multi-agent reinforcement learning

Vinyals, O., Babuschkin, I., Czarnecki, W. M., Mathieu, M., Dudzik, A., Chung, J., Choi, D. H., Powell, R., Ewalds, T., Georgiev, P., et al. (2019) · Nature · doi:10.1038/s41586-019-1724-z · Cited by 3,455 · see citing works

Markov Games as a Framework for Multi-Agent Reinforcement Learning

Littman, M. L. (1994) · International Conference on Machine Learning · doi:10.1016/b978-1-55860-335-6.50027-1 · Cited by 3,406 · see citing works

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Lowe, R., Wu, Y., Tamar, A., Harb, J., Abbeel, P., & Mordatch, I. (2017) · arXiv · doi:10.48550/arxiv.1706.02275 · Cited by 3,377 · see citing works

The Economy as an Evolving Complex System II

Arthur, W. B. (2018) · CRC Press eBooks · doi:10.1201/9780429496639 · Cited by 2,352 · see citing works

A Comprehensive Survey of Multiagent Reinforcement Learning

Busoniu, L., Babuska, R., & De Schutter, B. (2008) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2007.913919 · Cited by 2,235 · see citing works

Counterfactual Multi-Agent Policy Gradients

Foerster, J., Farquhar, G., Afouras, T., Nardelli, N., & Whiteson, S. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11794 · Cited by 1,873 · see citing works

Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and Applications

Nguyen, T. T., Nguyen, N. D., & Nahavandi, S. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.2977374 · Cited by 1,306 · see citing works

Multiagent systems: A survey from a machine learning perspective

Stone, P., & Veloso, M. (2000) · Autonomous Robots · doi:10.1023/a:1008942012299 · Cited by 1,218 · see citing works

System dynamics, systems thinking, and soft OR

Forrester, J. W. (1994) · System Dynamics Review · doi:10.1002/sdr.4260100211 · Cited by 1,117 · see citing works

Multiagent cooperation and competition with deep reinforcement learning

Tampuu, A., Matiisen, T., Kodelja, D., Kuzovkin, I., Korjus, K., Aru, J., Aru, J., & Vicente, R. (2017) · PLoS ONE · doi:10.1371/journal.pone.0172395 · Cited by 901 · see citing works

Asset Pricing Under Endogenous Expectations in an Artificial Stock MarketPreprint

Arthur, W. B., Holland, J. H., LeBaron, B. D., Palmer, R. G., & Tayler, P. (1997) · SSRN Electronic Journal · doi:10.2139/ssrn.2252 · Cited by 850 · see citing works

A survey and critique of multiagent deep reinforcement learning

Hernández-Leal, P., Kartal, B., & Taylor, M. E. (2019) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-019-09421-1 · Cited by 747 · see citing works

Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models

Rahmandad, H., & Sterman, J. D. (2008) · Management Science · doi:10.1287/mnsc.1070.0787 · Cited by 740 · see citing works

Business Dynamics—Systems Thinking and Modeling for a Complex World

Swanson, J. (2002) · Journal of the Operational Research Society · doi:10.1057/palgrave.jors.2601336 · Cited by 442 · see citing works

If multi-agent learning is the answer, what is the question?

Shoham, Y., Powers, R., & Grenager, T. (2007) · Artificial Intelligence · doi:10.1016/j.artint.2006.02.006 · Cited by 419 · see citing works

Autonomous agents modelling other agents: A comprehensive survey and open problems

Albrecht, S. V., & Stone, P. (2018) · Artificial Intelligence · doi:10.1016/j.artint.2018.01.002 · Cited by 417 · see citing works

Effective reinforcement learning for mobile robots

Smart, W. D., & Kaelbling, L. P. (2003) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2002.1014237 · Cited by 380 · see citing works

Learning Attentional Communication for Multi-Agent CooperationPreprint

Jiang, J., & Lu, Z. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.07733 · Cited by 372 · see citing works

Would-be worlds: How simulation is changing the frontiers of science

(1996) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(96)90002-4 · Cited by 358 · see citing works

Evolutionary Dynamics of Multi-Agent Learning: A Survey

Bloembergen, D., Tuyls, K., Hennes, D., & Kaisers, M. (2015) · Journal of Artificial Intelligence Research · doi:10.1613/jair.4818 · Cited by 301 · see citing works

A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning

Lanctot, M., Zambaldi, V., Gruslys, A., Lazaridou, A., Tuyls, K., Perolat, J., Silver, D., & Graepel, T. (2017) · arXiv · doi:10.48550/arxiv.1711.00832 · Cited by 295 · see citing works

Applications of agent-based models for optimization problems: A literature review

Barbati, M., Bruno, G., & Genovese, A. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.12.015 · Cited by 268 · see citing works

Growing Artificial Societies—Social Science from the Bottom Up.

Gessler, N. (1997) · Artificial Life · doi:10.1162/artl.1997.3.237 · Cited by 242 · see citing works

Parallel agent-based simulation with Repast for High Performance Computing

Collier, N. T., & NORTH, M. J. (2012) · SIMULATION · doi:10.1177/0037549712462620 · Cited by 219 · see citing works

Multiagent Systems: A Survey from a Machine Learning Perspective

Stone, P., & Veloso, M. (1997) · doi:10.21236/ada333248 · Cited by 205 · see citing works

Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement LearningPreprint

Papoudakis, G., Christianos, F., Rahman, A., & Albrecht, S. V. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.04737 · Cited by 176 · see citing works

Modeling technological innovation risks of an entrepreneurial team using system dynamics: An agent-based perspective

Wu, D. D., Kefan, X., Hua, L., Shi, Z., & Olson, D. L. (2010) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2010.01.015 · Cited by 151 · see citing works

Agent-based modeling and simulation: Desktop ABMS

Macal, C. M., & North, M. J. (2007) · Winter Simulation Conference · doi:10.1109/wsc.2007.4419592 · Cited by 151 · see citing works

Design classes for hybrid simulations involving agent-based and system dynamics models

Swinerd, C., & McNaught, K. R. (2012) · Simulation Modelling Practice and Theory · doi:10.1016/j.simpat.2011.09.002 · Cited by 146 · see citing works

An Agent-Based Microsimulation Model of Swiss Travel: First Results

Raney, B., Cetin, N., Voellmy, A., Vrtic, M., Axhausen, K. W., & Nagel, K. (2003) · Networks and Spatial Economics · doi:10.1023/a:1022096916806 · Cited by 141 · see citing works

Agent-based and system dynamics modeling: a call for cross study and joint research

Scholl, H. J. (2005) · Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · doi:10.1109/hicss.2001.926296 · Cited by 140 · see citing works

Hybrid simulation models – When, Why, How?

Lättilä, L., Hilletofth, P., & Lin, B. (2010) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.04.039 · Cited by 139 · see citing works

System Dynamics versus Agent-Based Modeling: A Review of Complexity Simulation in Construction Waste Management

Ding, Z., Gong, W., Li, S., & Wu, Z. (2018) · Sustainability · doi:10.3390/su10072484 · Cited by 135 · see citing works

Modeling Others using Oneself in Multi-Agent Reinforcement LearningPreprint

Răileanu, R., Denton, E., Szlam, A. D., & Fergus, R. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1802.09640 · Cited by 126 · see citing works

Using Agent-Based Modeling to Study Construction Labor Productivity as an Emergent Property of Individual and Crew Interactions

Watkins, M., Mukherjee, A., Onder, N., & Mattila, K. G. (2009) · Journal of Construction Engineering and Management · doi:10.1061/(asce)co.1943-7862.0000022 · Cited by 126 · see citing works

Adaptive agents, intelligence, and emergent human organization: Capturing complexity through agent-based modeling

Berry, B. J. L., Kiel, L. D., & Elliott, E. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.092078899 · Cited by 126 · see citing works

Emergent structures in supply chains - a study integrating agent-based and system dynamics modeling

Schieritz, N., & GroBler, A. (2003) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2003.1174226 · Cited by 122 · see citing works

Agent‐Based Modeling and Simulation

Klügl, F., & Bazzan, A. L. C. (2012) · AI Magazine · doi:10.1609/aimag.v33i3.2425 · Cited by 119 · see citing works

A Note on the Correspondence Between Complexity and Systems Theory

Phelan, S. E. (1999) · Systemic Practice and Action Research · doi:10.1023/a:1022495500485 · Cited by 108 · see citing works

Modeling Framework and Architecture of Hybrid System Dynamics and Discrete Event Simulation for Construction

Alvanchi, A., Lee, S. H., & AbouRizk, S. (2010) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/j.1467-8667.2010.00650.x · Cited by 105 · see citing works

Modeling the Forest or Modeling the Trees - A Comparison of System Dynamics and Agent-Based Simulation

Milling, P. M., & Schieritz, N. (2003) · Cited by 103 · see citing works

To agent-based simulation from System Dynamics

Macal, C. M. (2010) · Winter Simulation Conference · doi:10.1109/wsc.2010.5679148 · Cited by 99 · see citing works

Artificial Life Models in Software

Komosiński, M., & Adamatzky, A. (2009) · Springer eBooks · doi:10.1007/978-1-84882-285-6 · Cited by 93 · see citing works

Would-be worlds: how simulation is changing the frontiers of science

(1997) · Choice Reviews Online · doi:10.5860/choice.34-3354 · Cited by 77 · see citing works

Large-Scale Agent-Based Pedestrian Simulation

Klügl, F., & Rindsfüser, G. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-74949-3_13 · Cited by 71 · see citing works

Integrated Agent-based and System Dynamics Modelling for Simulation of Sustainable Mobility

Shafiei, E., Stefánsson, H., Ásgeirsson, E. I., Davíðsdóttir, B., & Raberto, M. (2012) · Transport Reviews · doi:10.1080/01441647.2012.745632 · Cited by 71 · see citing works

Making friends on the fly: Cooperating with new teammates

Barrett, S., Rosenfeld, A., Kraus, S., & Stone, P. (2016) · Artificial Intelligence · doi:10.1016/j.artint.2016.10.005 · Cited by 69 · see citing works

Neural network based model for predicting housing market performance

Khalafallah, A. (2008) · Tsinghua Science & Technology · doi:10.1016/s1007-0214(08)70169-x · Cited by 69 · see citing works

On quantum methods for machine learning problems part I: Quantum tools

Ablayev, F. M., Ablayev, M., Huang, J. Z., Khadiev, K. R., Salikhova, N., & Wu, D. (2019) · Big Data Mining and Analytics · doi:10.26599/bdma.2019.9020016 · Cited by 65 · see citing works

Intrusion detection system using voting-based neural network

Haghighat, M. H., & Li, J. (2021) · Tsinghua Science & Technology · doi:10.26599/tst.2020.9010022 · Cited by 60 · see citing works

A hybrid simulation framework for modelling construction projects using agent-based modelling and system dynamics: an application to model construction workers' safety behavior

Nasirzadeh, F., Khanzadi, M., & Mir, M. (2017) · International Journal of Construction Management · doi:10.1080/15623599.2017.1285485 · Cited by 59 · see citing works

A comparative analysis of parallel processing and super-individual methods for improving the computational performance of a large individual-based model

Parry, H. R., & Evans, A. J. (2008) · Ecological Modelling · doi:10.1016/j.ecolmodel.2008.02.002 · Cited by 47 · see citing works

System dynamics approach for construction risk analysis

Nasirzadeh, F., Afshar, A., & Khanzadi, M. (2008) · Cited by 46 · see citing works

Hybrid simulation with loosely coupled system dynamics and agent-based models for Prospective Health Technology Assessments

Djanatliev, A., German, R., Kolominsky‐Rabas, P. L., & Hofmann, B. (2012) · Winter Simulation Conference · doi:10.1109/wsc.2012.6465024 · Cited by 42 · see citing works

Intelligent cognitive spectrum collaboration: Convergence of spectrum sensing, spectrum access, and coding technology

Cai, P., & Zhang, Y. (2020) · Intelligent and Converged Networks · doi:10.23919/icn.2020.0006 · Cited by 41 · see citing works

Data-based Suboptimal Neuro-control Design with Reinforcement Learning for Dissipative Spatially Distributed Processes

Luo, B., Wu, H., & Li, H. (2014) · Industrial & Engineering Chemistry Research · doi:10.1021/ie4031743 · Cited by 39 · see citing works

Parallelization Strategies for Spatial Agent-Based Models

Fachada, N., Lopes, V. V., Martins, R. C., & Rosa, A. C. (2016) · International Journal of Parallel Programming · doi:10.1007/s10766-015-0399-9 · Cited by 38 · see citing works

Thinking quickly: Agents for modeling air warfare

Heinze, C., Smith, B., & Cross, M. (1998) · Lecture notes in computer science · doi:10.1007/bfb0095040 · Cited by 29 · see citing works

Towards a standard model for research in agent-based modeling and simulation

Fachada, N., Lopes, V. V., Martins, R. C., & Rosa, A. C. (2015) · PeerJ Computer Science · doi:10.7717/peerj-cs.36 · Cited by 22 · see citing works

ZenLDA: Large-scale topic model training on distributed data-parallel platform

Zhao, B., Zhou, H., Li, G., & Huang, Y. (2018) · Big Data Mining and Analytics · doi:10.26599/bdma.2018.9020006 · Cited by 21 · see citing works

Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?Preprint

Raghu, M., Irpan, A., Andreas, J., Kleinberg, R., Le, Q. V., & Kleinberg, J. M. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1711.02301 · Cited by 21 · see citing works

Coupling agent-based with equation-based models to study spatially explicit megapopulation dynamics

Marilleau, N., Lang, C., & Giraudoux, P. (2018) · Ecological Modelling · doi:10.1016/j.ecolmodel.2018.06.011 · Cited by 20 · see citing works

The residual gradient FACL algorithm for differential games

Awheda, M. D., & Schwartz, H. M. (2015) · Conference proceedings - Canadian Conference on Electrical and Computer Engineering · doi:10.1109/ccece.2015.7129412 · Cited by 19 · see citing works

Abductive Fallacies with Agent-Based Modeling and System Dynamics

Lorenz, T. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-01109-2_11 · Cited by 18 · see citing works

Development of Aspen: A microanalytic simulation model of the US economy

Sandia National Labs., A., Pryor, R. J., USDOE, W., Basu, N., & Quint, T. (1996) · doi:10.2172/204675 · Cited by 17 · see citing works

Soar-RWA: Planning, Teamwork, and Intelligent Behavior for Synthetic Rotary Wing Aircraft

Hill, J. R. W., Chen, J., Gratch, J. S., Rosenbloom, P. S., & Tambe, M. (1998) · Cited by 16 · see citing works

Visual perception-based fault diagnosis in froth flotation using statistical approaches

Zhang, J., Tang, Z., Xie, Y., Ai, M., & Gui, W. (2020) · Tsinghua Science & Technology · doi:10.26599/tst.2019.9010071 · Cited by 16 · see citing works

Massive Multi-agent Data-Driven Simulations of the GitHub Ecosystem

Blythe, J., Bollenbacher, J., Huang, D., Hui, P.-M., Krohn, R., Pacheco, D. F., Muric, G., Sapienza, A., Tregubov, A., Ahn, Y., et al. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-24209-1_1 · Cited by 14 · see citing works

The Emergence of Parties

Schreiber, D. M. (2013) · Political Research Quarterly · doi:10.1177/1065912913487258 · Cited by 13 · see citing works

Large-Scale Agent-Based Transport Simulation in Shanghai, China

Zhang, L., Yang, W., Wang, J., & Rao, Q. (2013) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/2399-04 · Cited by 13 · see citing works

Large-scale multi-agent mobility simulations on a GPU: towards high performance and scalability

Saprykin, A., Chokani, N., & Abhari, R. S. (2019) · Procedia Computer Science · doi:10.1016/j.procs.2019.04.098 · Cited by 12 · see citing works

Heterogeneous parallel algorithm design and performance optimization for WENO on the Sunway Taihulight supercomputer

Huang, J., Han, W., Wang, X., & Chen, W. (2019) · Tsinghua Science & Technology · doi:10.26599/tst.2018.9010112 · Cited by 12 · see citing works

A Massive Multi-agent System for Brain MRI Segmentation

Haroun, R., Boumghar, F. O., Hassas, S., & Hamami, L. (2005) · Lecture notes in computer science · doi:10.1007/11512073_13 · Cited by 11 · see citing works

Consensus of second-order multi-agent systems with time-varying delays and antagonistic interactions

Hou, B., Sun, F., Li, H., & Liu, G. (2015) · Tsinghua Science & Technology · doi:10.1109/tst.2015.7085634 · Cited by 9 · see citing works

A comparison between system dynamics and agent based modeling and opportunities for cross-fertilization

Stemate, L., Pasca, C., & Taylor, I. W. (2007) · doi:10.5555/1351542.1351976 · Cited by 9 · see citing works

Optimal Adaptive Control and Differential Games by Reinforcement Leanring Principles [Book review]

Dixon, W. E. (2014) · IEEE Control Systems · doi:10.1109/mcs.2014.2308694 · Cited by 9 · see citing works

Juxtaposition of System Dynamics and Agent-Based Simulation for a Case Study in Immunosenescence

Figueredo, G. P., Siebers, P., Aickelin, U., Whitbrook, A. M., & Garibaldi, J. M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0118359 · Cited by 7 · see citing works

A System Dynamics and Agent-Based Approach to Model Emotions in Collaborative Networks

Ferrada, F., & Camarinha-Matos, L. M. (2017) · IFIP advances in information and communication technology · doi:10.1007/978-3-319-56077-9_3 · Cited by 7 · see citing works

Experience Sharing Between Cooperative Reinforcement Learning Agents

Souza, L. O., Ramos, G. D. O., & Ralha, C. G. (2019) · IEEE International Conference on Tools with Artificial Intelligence (ICTAI) · doi:10.1109/ictai.2019.00136 · Cited by 7 · see citing works

Summarization of Agent-Based Modeling and Simulation

Jin-hai, D. (2008) · Jisuanji fangzhen · Cited by 7 · see citing works

A multiagent urban traffic simulationPreprint

Tranouez, P., Daudé, É., & Langlois, P. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1201.5472 · Cited by 7 · see citing works

Massive Multi-agent systems control

Campagne, J.-C., Cardon, A., Collomb, E., & Nishida, T. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30960-4_20 · Cited by 6 · see citing works

Reinforcement Learning Technology in Multi-Agent System

Zhao, Z. (2004) · Cited by 5 · see citing works

Including public transportation into a large-scale agent-based model for epidemic prediction and control

Zhang, M., Meng, R., & Verbraeck, A. (2015) · doi:10.5555/2874916.2874948 · Cited by 5 · see citing works

Decentralized Adaptive Optimal Control for Massive Multi-agent Systems Using Mean Field Game with Self-Organizing Neural Networks

Zhou, Z., & Xu, H. (2019) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc40024.2019.9029540 · Cited by 5 · see citing works

Towards billion-scale social simulations

Suzumura, T., Houngkaew, C., & Kanezashi, H. (2014) · Winter Simulation Conference · doi:10.1109/wsc.2014.7019940 · Cited by 5 · see citing works

Creating GPU-Enabled Agent-Based Simulations Using a PDES Tool

Marurngsith, W., & Mongkolsin, Y. (2013) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-00551-5_28 · Cited by 4 · see citing works

Intrusion detection system using voting based neural network

Sai, R. V., Saran, T., & Sundaram, G. (2022) · International Journal of Health Sciences · doi:10.53730/ijhs.v6ns5.9887 · Cited by 3 · see citing works

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

Schryver, J. C., Nutaro, J. J., & Shankar, M. A. (2015) · Open Journal of Modelling and Simulation · doi:10.4236/ojmsi.2015.34019 · Cited by 2 · see citing works

Realization of ACS in Repast

Wu, X. (2007) · Journal of Wuhan University of Technology-Mater Sci Ed · Cited by 1 · see citing works

Transportation 5.0: The DAO to Safe, Secure, and Sustainable Intelligent Transportation Systems

Wang, F., Lin, Y., Ioannou, P., Vlacic, L., Liu, X., Eskandarian, A., Lv, Y., Na, X., Cebon, D., Ma, J., et al. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3305380 · Cited by 216 · see citing works

Intelligent technologies for construction machinery using data-driven methods

Zheng, Z., Wang, F., Gong, G., Yang, H., & Han, D.-S. (2022) · Automation in Construction · doi:10.1016/j.autcon.2022.104711 · Cited by 78 · see citing works

Multimodal Agent AI: A Survey of Recent Advances and Future Directions

Sun, Y., Sun, H., Ma, J., Zhang, P., & Huang, X. (2025) · Journal of Computer Science and Technology · doi:10.1007/s11390-025-4802-8 · Cited by 69 · see citing works

Zooming in and out the landscape: Artificial intelligence and system dynamics in business and management

Armenia, S., Franco, E., Iandolo, F., Maielli, G., & Vito, P. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.123131 · Cited by 46 · see citing works

A foundational architecture for AI agents in healthcare

Liu, F., Niu, Y., Zhang, Q., Wang, K., Dong, Z., Wong, I. N., Cheng, L., Li, T., Duan, L., Li, K., et al. (2025) · Cell Reports Medicine · doi:10.1016/j.xcrm.2025.102374 · Cited by 41 · see citing works

Multi-Agent Embodied Visual Semantic Navigation With Scene Prior Knowledge

Liu, X., Guo, D., Liu, H., & Sun, F. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3145964 · Cited by 38 · see citing works

Unlocking AI Creativity: A Multi-Agent Approach with CrewAI

Venkadesh, P., Divya, S. V., & Kumar, K. (2024) · Journal of Trends in Computer Science and Smart Technology · doi:10.36548/jtcsst.2024.4.002 · Cited by 26 · see citing works

Artificial Intelligence in Mathematical Modeling of Complex Systems

Zhao, T. (2024) · ICST Transactions on e-Education and e-Learning · doi:10.4108/eetel.5256 · Cited by 19 · see citing works

A Matching Algorithm with Reinforcement Learning and Decoupling Strategy for Order Dispatching in On-Demand Food Delivery

Chen, J., Wang, L., Pan, Z., Wu, Y., Zheng, J., & Ding, X. (2023) · Tsinghua Science & Technology · doi:10.26599/tst.2023.9010069 · Cited by 15 · see citing works

Emergency mobile energy storage optimal allocation in microgrid-integrated distribution networks considering economic and resilience benefits

Liu, Z., Zhang, Y., & Ning, Y. (2025) · Energy · doi:10.1016/j.energy.2025.135633 · Cited by 13 · see citing works

On the Innovative Work and Development of Library Reader Service in the Era of Artificial Intelligence

Zhang, X. (2022) · Wireless Communications and Mobile Computing · doi:10.1155/2022/3779660 · Cited by 12 · see citing works

Multi-Agent-Based Simulation of Intelligent Network System

Tshakwanda, P. M., Arzo, S. T., & Devetsikiotis, M. (2023) · IEEE Annual Computing and Communication Workshop and Conference (CCWC) · doi:10.1109/ccwc57344.2023.10099195 · Cited by 10 · see citing works

QAPP: A quality-aware and privacy-preserving medical image release scheme

Zhang, X., Wang, Y., Ma, J., & Jin, Q. (2022) · Information Fusion · doi:10.1016/j.inffus.2022.07.011 · Cited by 9 · see citing works

Agent-based modeling and simulation for 5G and beyond networks : A comprehensive survey

Shakya, J., Ghribi, C., & Merghem, L. (2023) · Simulation Modelling Practice and Theory · doi:10.1016/j.simpat.2023.102855 · Cited by 9 · see citing works

Joint optimization algorithm for vehicle scheduling and supply chain inventory management based on multi-agent deep reinforcement learning

Feng, L. (2025) · Neural Computing and Applications · doi:10.1007/s00521-025-11661-0 · Cited by 8 · see citing works

AI agent-driven process automation for dynamic production efficiency and intelligent equipment integration

Chen, C., & Lin, S.-C. (2025) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-025-02706-1 · Cited by 8 · see citing works

From the logic of coordination to goal-directed reasoning: the agentic turn in artificial intelligence

Haidemariam, T. (2026) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1728738 · Cited by 8 · see citing works

Periodic Intermittent Adaptive Control with Saturation for Pinning Quasi-Consensus of Heterogeneous Multi-Agent Systems with External Disturbances

Du, B., Xu, Q., Zhang, J., Tang, Y., Wang, L., Yuan, R., Yuan, Y., & An, J. (2023) · Entropy · doi:10.3390/e25091266 · Cited by 5 · see citing works

Improving the Resource Allocation in IoT Systems Based on the Integration of Reinforcement Learning and Rule-Based Approaches in Multi-agent Systems

Yarahmadi, H., Navidi, H., & Challenger, M. (2024) · International Conference on Smart Cities, Internet of Things and Applications (SCIoT) · doi:10.1109/sciot62588.2024.10570102 · Cited by 5 · see citing works

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Nanda, P., Sahoo, S., Rodríguez-Aguilar, R., Marmolejo-Saucedo, J. A., & Behera, I. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-21905-4.00011-0 · Cited by 4 · see citing works

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Chen, G., Ming, Z., Milisavljevic-Syed, J., Xia, H., Salonitis, K., Wang, G., & Yan, Y. (2025) · Advanced Engineering Informatics · doi:10.1016/j.aei.2025.103494 · Cited by 4 · see citing works

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Tayal, C., Murumkar, S., & Biradar, S. S. (2026) · IEEE Annual Computing and Communication Workshop and Conference (CCWC) · doi:10.1109/ccwc67433.2026.11393746 · Cited by 4 · see citing works

Energy-efficient Pump Control in Industrial Cooling Water Systems Using a Multi-Agent System

Borst, F., Theisinger, L., & Weigold, M. (2023) · Procedia CIRP · doi:10.1016/j.procir.2023.02.008 · Cited by 4 · see citing works

Configurable Intelligent Design Based on Hierarchical Imitation Models

Yavich, R., Malev, S., Volinsky, I., & Rotkin, V. (2023) · Applied Sciences · doi:10.3390/app13137602 · Cited by 4 · see citing works

Advanced Systems Engineering

Riedel, O., Kürümlioglu, M., & Schneider, B. (2023) · Springer eBooks · doi:10.1007/978-3-642-45370-0_132-1 · Cited by 4 · see citing works

Utilizing Agent-Based Modeling for Optimization of Wayfinding in Hospital: A Case Study

Khasraghi, G. S., & Nejat, A. (2024) · HERD Health Environments Research & Design Journal · doi:10.1177/19375867241248593 · Cited by 4 · see citing works

Simulation of An Automatic System of Robotics for Artificial Animated Being Manufacturing Using AnyLogic Simulation Software

Bashabsheh, M. (2024) · International Journal of Electrical and Electronics Engineering · doi:10.14445/23488379/ijeee-v11i5p112 · Cited by 4 · see citing works

Improve steganography system using agents software based on statistical and classification technique

Halboos, E. H. J., & Al-Bakry, A. M. (2023) · Bulletin of Electrical Engineering and Informatics · doi:10.11591/eei.v12i3.4540 · Cited by 3 · see citing works

МУЛЬТИАГЕНТНІ СИСТЕМИ В УПРАВЛІННІ АКАДЕМІЧНИМИ УСТАНОВАМИ

Гужва, В. М. (2025) · Сталий розвиток економіки · doi:10.32782/2308-1988/2024-51-39 · Cited by 3 · see citing works

The protection of the natural environment in armed conflicts and agent-based modelling

Qandeel, M. (2023) · International Review of the Red Cross · doi:10.1017/s1816383123000528 · Cited by 3 · see citing works

Artificial intelligence and EEG during anesthesia: ideal match or fleeting bond?

Introna, M., Karippacheril, J. G., Pilla, S., Trimarchi, D., Gemma, M. F., Martino, D., & Carozzi, C. (2026) · Artificial Intelligence Surgery · doi:10.20517/ais.2025.68 · Cited by 2 · see citing works

Humanoid Five-Digit Robotic Grasping via Multi-Agent Reinforcement Learning With Potential-Guided Optimization and Weight Scheduling

Wang, J., Li, K., Wang, X., Li, G., Li, Z., Zhang, N., Liu, M., & Wei, N. (2026) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2026.3672621 · Cited by 2 · see citing works

Multi-agent systems modeling of command and control systems: a metrics-driven approach to simulator evaluation and co-simulation

de Carvalho, L. F. B. S., de Souza, V. S., Bonatto, A. N., Perez, T., Barone, D. A. C., Wickboldt, J. A., dos Anjos, J. C. S., Fernandes, R. Q. D. A., & de Freitas, E. P. (2025) · Journal of Simulation · doi:10.1080/17477778.2025.2584542 · Cited by 1 · see citing works

Multi-Agent AI Simulation for Evaluating Sustainability of Urban Transportation Infrastructure

James, E., & Martinez, S. (2025) · Civil Engineering Science and Technology · doi:10.51903/tx30kz14 · Cited by 1 · see citing works

Modeling and Simulation Challenges for Cyber Physical Systems from Operational Security Perspective

Rahim, K., & Qureshi, H. K. (2021) · International Conference on Cyber Warfare and Security (ICCWS) · doi:10.1109/iccws53234.2021.9703029 · Cited by 1 · see citing works

A Next-Gen Approach to Streamlined Canteen Management Systems using Mesa Framework

Narendran, A., Inuguri, A. H., Manyam, Y., Sundaram, S., & Khanna, M. (2024) · International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS) · doi:10.1109/csitss64042.2024.10816849 · Cited by 1 · see citing works

Keywords-Driven Paper Recommendation Based on Mobile Edge Computing Environment Framework

Liu, H., Wang, S., Ren, H., Meng, S., Hou, J., & Li, Q. (2022) · Scientific Programming · doi:10.1155/2022/3943419

Site selection optimization method for terminals of specially regulated vessels based on scenario simulation

Shen, C., Hao, J., Fang, Z., Guo, Y., Tang, G., Ding, W., & Wang, D. (2024) · doi:10.1145/3686812.3686823

Controle de Tráfego Aéreo Autônomo: Simulação de Sistemas Multiagentes com o framework JaCaMo na plataforma Unity

VIERO, B. D. S., Bordini, R. H., & Zamberlan, A. D. O. (2024) · Anais do Workshop-Escola de Sistemas de Agentes, seus Ambientes e Aplicações (WESAAC) · doi:10.5753/wesaac.2024.33461

Agentic traffic intelligence: Augmented human-in-the-loop scenario generation for microscopic traffic simulation

Luo, X., Xu, G., Saroj, A., Yuan, J., Kadav, P., Shao, Y., & Wang, C. R. (2026) · Artificial Intelligence for Transportation · doi:10.1016/j.ait.2026.100057

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Altun, O., & Fişne, E. (2026) · Journal of Polytechnic · doi:10.2339/politeknik.1770179

An Urban Waterlogging Dynamic Vulnerability Assessment Framework Integrating Hydrological-hydrodynamic Model, Multi-agent Modeling, and the Choquet Integral

Yang, W., Li, M., Jiang, X., Hu, D., Liang, H., Jiang, X., & Liu, X. (2026) · Water Resources Management · doi:10.1007/s11269-026-04499-1

Research on Intelligent AI-Based Telephone Billing System Architecture and Application in Utility Services

Qiao, X., Lai, X., Fan, X., Yu, W., Li, J., Meng, P., Dong, H., & Anqi, Y. (2026) · IEEE International Conference on Power, Electronics and Green Energy (ICPEGE) · doi:10.1109/icpege67691.2026.11451373

Méthodes, modèles et outils pour la conception, la simulation et la programmation de systèmes robotiques modulaires et cyber-physiques

Jimenez, L. (2022) · theses.fr (ABES) · doi:10.70675/36118eb5zd9afz4bbdzad54zfb535c9c08d6

LeakAgent: a multi-agent system for automated water pipe leak detection

Tu, L., Bai, L., Rayhana, R., Ling, J., Liu, Z., & Kong, X. (2026) · Digital Twins, AI, and NDE for Industry Applications and Energy Systems · doi:10.1117/12.3089533

Application for Modeling the Process of Heat Loss Through a Multilayer Building Wall

Bazurin, V. M., Pursky, O. I., Підгорна, Т. В., & Tomashevska, T. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-24926-5_27

IPMMO: An Exploratory Benchmark for Information Propagation Optimization

Gu, G., Zuo, W., Zhao, T.-F., Wu, X.-K., & Chen, W. (2026) · Communications in computer and information science · doi:10.1007/978-981-95-9877-9_17

Agent-Based Modeling of Household Energy Consumption in the Districts of Ouagadougou

Coulibaly, D., Belem, M., & Ouedraogo, Y. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-27563-9_36

System Dynamics Meets Multi-Agent Systems: A Review of Hybrid Simulation Approaches

Samuil, I., Ionica, A. C., & Leba, M. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-32032-2_22

Review of AI agents in engineering design workflows

McCreery, Z., & Naser, M. Z. (2026) · Automation in Construction · doi:10.1016/j.autcon.2026.107305

Mass programmed agents for simulating human strategies in large scale systems

Chalamish, M., Sarne, D., & Kraus, S. (2007) · Adaptive Agents and Multi-Agents Systems · doi:10.1145/1329125.1329291 · Cited by 7 · see citing works

Multi-agent systems simulation and applications

Uhrmacher, A. M., & Weyns, D. (2009) · Cited by 20 · see citing works

Artificial Intelligence in Modeling and Simulation

Zeigler, B. P., Muzy, A., & Yılmaz, L. (2009) · Springer eBooks · doi:10.1007/978-0-387-30440-3_24 · Cited by 15 · see citing works

Multi-agent systems: theory and applications survey

Naciri, N., & Tkiouat, M. (2015) · International Journal of Intelligent Systems Technologies and Applications · doi:10.1504/ijista.2015.074078 · Cited by 11 · see citing works

Preliminary research on modeling and simulation technology of artificial intelligence system

Li, K., & Liu, L. (2018) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/452/4/042003 · Cited by 2 · see citing works