Gotowe bibliografie tematyczne / Artificial Intelligence in Civil Engineering

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Gotowa bibliografia na temat „Artificial Intelligence in Civil Engineering”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Artificial Intelligence in Civil Engineering"

Lu, Pengzhen, Shengyong Chen, and Yujun Zheng. "Artificial Intelligence in Civil Engineering." Mathematical Problems in Engineering 2012 (2012): 1–22. http://dx.doi.org/10.1155/2012/145974.

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Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural network

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Dede, Tayfun, Murat Kankal, Ali Reza Vosoughi, Maksym Grzywiński, and Moacir Kripka. "Artificial Intelligence Applications in Civil Engineering." Advances in Civil Engineering 2019 (May 2, 2019): 1–3. http://dx.doi.org/10.1155/2019/8384523.

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Shaktisinh, D. Gohil. "Artificial Intelligence: Transforming Civil Engineering Applications." Journal of Building Construction 7, no. 2 (2025): 9–24. https://doi.org/10.5281/zenodo.14986239.

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Artificial Intelligence (AI) is a subfield of computer science focused on the study, creation, and application of intelligent systems. While solving complex problems often requires immense computational power, AI technologies provide a more efficient alternative. This includes the development and implementation of AI in civil engineering, offering insights into recent innovations and advancements in the field. With the rapid progress in big data, deep learning, and machine learning technologies, AI is being increasingly applied across various sectors of civil engineering.  </

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Du, Ping, and Weijian Che. "Research on Discipline Construction of Civil Engineering Based on Artificial Intelligence." Advances in Engineering Technology Research 6, no. 1 (2023): 254. http://dx.doi.org/10.56028/aetr.6.1.254.2023.

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Artificial intelligence is gradually changing the development direction of civil engineering, and the traditional civil engineering specialty needs to be transformed. This paper discusses the application of artificial intelligence technology in the field of civil engineering, and analyzes the opportunities and challenges brought by the combination of artificial intelligence and civil engineering. A feasible scheme for the integration of artificial intelligence and civil engineering disciplines is proposed to help civil engineering majors better adapt to market demand and technological developm

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Lagaros, Nikos D., and Vagelis Plevris. "Artificial Intelligence (AI) Applied in Civil Engineering." Applied Sciences 12, no. 15 (2022): 7595. http://dx.doi.org/10.3390/app12157595.

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More, Pratik. "Application of Artificial Intelligence in Civil Engineering." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 5170–72. https://doi.org/10.22214/ijraset.2025.69458.

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This study explores the application of Artificial Intelligence (AI) in movable dividers in civil engineering. By integrating AI with movable dividers, we can create smart, adaptable spaces that optimize space usage, acoustic performance, and energy efficiency. AI-powered movable dividers can automatically adjust to changing environmental conditions, predict maintenance needs, and provide insights on space usage and occupant behavior. This technology has the potential to revolutionize the design and operation of buildings, events, and exhibitions, enabling more efficient, safe, and flexible use

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Srushti, Chute Priyanka Soni Megha Salve. "Uses of Artificial Intelligence in Civil Engineering." International Journal of Advanced Innovative Technology in Engineering 10, no. 2 (2025): 45–51. https://doi.org/10.5281/zenodo.15387634.

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Artificial Intelligence (AI), a branch of computer science, focuses on the development and application of intelligent systems. Solving complex problems typically demands substantial computational power, but AI-driven technologies offer a more efficient alternative. This paper explores recent advancements in AI concepts and methodologies within civil engineering, highlighting the field’s rapid progress. With significant developments in big data, deep learning, and machine learning, AI has been effectively integrated into various domains of civil engineering. Key areas of AI research in th

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Xie, Chengbo. "Research on the application of artificial intelligence in civil engineering monitoring." Advances in Engineering Technology Research 5, no. 1 (2023): 508. http://dx.doi.org/10.56028/aetr.5.1.508.2023.

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As the core basis of industrial reform in the new era, artificial intelligence can improve the development level of informatization, automation and intelligence in the field of civil engineering, and lay the foundation for the creation of a technical system with the value of The Times. In recent years, integrated research on the integration development trend between artificial intelligence and civil engineering, clear the basic research field of artificial intelligence, use visual tools to excavate the main problems and development bottlenecks of artificial intelligence in the field of civil e

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张, 德洋. "Innovative Application of Artificial Intelligence in Civil Engineering." Hans Journal of Civil Engineering 13, no. 08 (2024): 1444–53. http://dx.doi.org/10.12677/hjce.2024.138156.

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Xie, Ming, Fanbing Meng, Jingya Zou, Wei Feng, and Shaohua Ma. "Application of Artificial Intelligence in Civil Engineering Education." Journal of Physics: Conference Series 1575 (June 2020): 012225. http://dx.doi.org/10.1088/1742-6596/1575/1/012225.

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Rozprawy doktorskie na temat "Artificial Intelligence in Civil Engineering"

Gkiokas, Alexandros. "Imitation learning in artificial intelligence." Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/94683/.

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Acquiring new knowledge often requires an agent or a system to explore, search and discover. Yet us humans build upon the knowledge of our forefathers, as did they, using previous knowledge; there does exist a mechanism which allows transference of knowledge without searching, exploration or discovery. That mechanism is known as imitation and it exists everywhere in nature; in animals, insects, primates, and humans. Enabling artificial, cognitive and software agents to learn by imitation could potentially be crucial to the emergence of the field of autonomous systems, robotics, cyber-physical

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Gwyn, Bryan James. "The use of artificial intelligence techniques for power analysis." Thesis, City University London, 1999. http://openaccess.city.ac.uk/8281/.

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This thesis reports the research carried out into the use of Artificial Intelligence techniques for Power System Analysis. A number of aspects of Power System analysis and its management are investigated and the application of Artificial Intelligence techniques is researched. The use of software tools for checking the application of power system protection systems particularly for complex circuit arrangements was investigated. It is shown that the software provides a more accurate and efficient way of carrying out these investigations. The National Grid Company's (plc, UK) use of software tool

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Nijem, Abdelaziz. "ARTIFICIAL INTELLIGENCE NEURAL NETWORK: COMPRESSIVE STRENGTH PREDICTION OF RECYCLED AGGREGATE CONCRETE SAMPLES." Cleveland State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=csu161022170304632.

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Chen, Su Liang. "Development of automated bearing condition monitoring using artificial intelligence techniques." Thesis, University of Southampton, 2009. https://eprints.soton.ac.uk/195557/.

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A recent series of tapered roller bearing tests have been conducted at the University of Southampton to evaluate the effectiveness of using multiple sensing technologies to detect incipient faults. The test rig was instrumented with on-line sensors including vibration, temperature and electrostatic wear and oil-line debris sensors. Off-line techniques were also used such as debris analysis and bearing surface examination. The electrostatic sensors, in particular, have the potential to detect early decay of tribological contacts within rolling element bearings. These sensors have the unique abi

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Liu, Zihuai. "Artificial intelligence infrastructure into material attributes insights." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/126909.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020 Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020 Cataloged from the official PDF of thesis. Includes bibliographical references (pages 57-60). The development of a biopharmaceutical manufacturing process involves an assessment of all possible sources of variation throughout each of the uni

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Calado, Joao Manuel Ferreira. "On-line fault diagnosis of industrial processes based on artificial intelligence techniques." Thesis, City University London, 1996. http://openaccess.city.ac.uk/7773/.

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In this research the application of artificial intelligence techniques for on-line process control and fault detection and diagnosis are investigated. The majority of the research is on using artificial intelligence techniques in on-line fault detection and diagnosis of industrial processes. Several on-line approaches, including a rule based controller and several fault detection and diagnosis systems, have been developed and implemented and are described throughout this thesis. The research results obtained demonstrate that rule based controllers can be an alternative in situations where conv

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Lo, Kin-keung. "An investigation of computer assisted testing for civil engineering students in a Hong Kong technical institute." Click to view the E-thesis via HKUTO, 1988. http://sunzi.lib.hku.hk/HKUTO/record/B38627000.

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Uraz, Irtek. "Optimization Of Well Placement In Complex Carbonate Reservoirs Using Artificial Intelligence." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12605893/index.pdf.

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This thesis proposes a framework for determining the optimum location of an injection well by using an inference method, Artificial Neural Networks and a search algorithm to create a search space and locate the global maxima. Theoretical foundation of the proposed framework is followed by description of the field for case study. A complex carbonate reservoir, having a recorded geothermal production history is used to evaluate the proposed framework ( Kizildere Geothermal field, Turkey). In the proposed framework, neural networks are used as a tool to replicate the behavior of commercial simula

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Burton, Holly. "Reservoir inflow forecasting using time series and neural network models." Thesis, McGill University, 1998. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=29800.

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In practice, the reservoir net inflow is computed based upon the application of the water balance equation to the reservoir system since it is difficult to obtain direct and reliable measurements of this variable. The net inflow process has been thus found to possess a random behaviour because it is related to the stochastic nature of various physical processes involved in the water balance computation (e.g., precipitation, evaporation, etc.). Therefore, the aim of this research is to propose a forecasting method that can accurately and efficiently predict the random reservoir inflow series. T

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Abbas, Syed Murtuza. "Advanced Hybrid Simulation Model based on Phenomenology and Artificial Intelligence." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427963095.

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Książki na temat "Artificial Intelligence in Civil Engineering"

Topping, B. H. V. 1952-, ed. Artificial intelligence and civil engineering. Civil-Comp, 1991.

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Momeni, Ehsan, Danial Jahed Armaghani, and Aydin Azizi, eds. Artificial Intelligence in Mechatronics and Civil Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8790-8.

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B, Kumar, and Topping B. H. V, eds. Artificial intelligence applications in civil and structural engineering. Civil-Comp, 1999.

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Topping, B. H. V., ed. Optimization and Artificial Intelligence in Civil and Structural Engineering. Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-017-2490-6.

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Topping, B. H. V., ed. Optimization and Artificial Intelligence in Civil and Structural Engineering. Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-017-2492-0.

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V, Topping B. H., ed. Optimization and artificial intelligence in civil and structural engineering. Kluwer Academic, 1992.

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V, Topping B. H., International Conference on Civil, Structural and Environmental Engineering Computing (11th : 2007 : St. Julians, Malta), and International Conference on the Application of Artificial Intelligence to Civil, Structural, and Environmental Engineering (9th : 2007 : St. Julians, Malta), eds. Civil engineering computations: Tools and techniques. Saze-Coburg Publications, 2007.

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EuropIA International Conference on the Application of Artificial Intelligence, Robotics, and Image Processing to Architecture, Building Engineering, Civil Engineering, Urban Design, and Urban Planning (4th 1993 Delft, Netherlands). Advanced technologies: Architecture, planning, civil engineering. Elsevier, 1993.

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Li, Lijuan. Group Search Optimization for Applications in Structural Design. Springer Berlin Heidelberg, 2011.

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International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering (7th 2003 Egmond aan Zee, Netherlands). Proceedings of the seventh International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering: [Egmond-aan-Zee, the Netherlands, 2-4 September 2003]. Civil-Comp Press, 2003.

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Części książek na temat "Artificial Intelligence in Civil Engineering"

Zhang, Limao, Yue Pan, Xianguo Wu, and Mirosław J. Skibniewski. "Introduction to Artificial Intelligence." In Lecture Notes in Civil Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2842-9_1.

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Alp, Sina. "Micromobility and Artificial Intelligence." In Springer Tracts in Civil Engineering. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-77098-2_20.

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Wu, Gang, ZhiQiang Chen, and Ji Dang. "Machine Learning and Artificial Intelligence." In Springer Tracts in Civil Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3827-4_6.

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Samui, Pijush. "Artificial Intelligence in Offshore Infrastructure." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3912-0_2.

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Mahajan, Lomesh S., Monali Kirange, and Ganesh Suryawanshi. "An Artificial Intelligence Applications in Structural Engineering." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3994-3_15.

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Rustell, Michael. "Artificial Intelligence and Data in Civil Engineering." In Innovation in Construction. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95798-8_8.

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Souza, Leonardo, and Purnanand Savoikar. "Need for Artificial Intelligence in Geotechnical Earthquake Engineering." In Lecture Notes in Civil Engineering. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5669-9_35.

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Luckey, Daniel, Henrieke Fritz, Dmitrii Legatiuk, Kosmas Dragos, and Kay Smarsly. "Artificial Intelligence Techniques for Smart City Applications." In Lecture Notes in Civil Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51295-8_1.

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Awolusi, Temitope Funmilayo, Bernard Chukwuemeka Finbarrs-Ezema, Isaac Munachimdinamma Chukwudulue, and Marc Azab. "Application of Artificial Intelligence (AI) in Civil Engineering." In Studies in Systems, Decision and Control. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65976-8_2.

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Ocak, Ayla, Sinan Melih Nigdeli, Gebrail Bekdaş, and Ümit Işıkdağ. "Artificial Intelligence and Deep Learning in Civil Engineering." In Studies in Systems, Decision and Control. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-34728-3_13.

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Streszczenia konferencji na temat "Artificial Intelligence in Civil Engineering"

Marupov, Azizkhon, Kosimkhon Makhsimov, Ravshanjon Mirzaev, Ozodbek Tursunov, Makhmud Bakhromov, and Bahodirjon Eminchaev. "Smart Structures: Leveraging Artificial Intelligence for Sustainable Solutions in Civil Engineering." In 2024 4th International Conference on Advancement in Electronics & Communication Engineering (AECE). IEEE, 2024. https://doi.org/10.1109/aece62803.2024.10911280.

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Lai, Zhenhuan. "Artificial Intelligence-Based Computational Analysis and Optimization of Civil Engineering Structures." In 2024 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE). IEEE, 2024. https://doi.org/10.1109/icaice63571.2024.10864138.

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Wang, Zhaogang, and Jianqiao Zhang. "Application and Optimization of Artificial Intelligence Algorithms in Cost Management in Civil Engineering." In 2024 3rd International Conference on Data Analytics, Computing and Artificial Intelligence (ICDACAI). IEEE, 2024. https://doi.org/10.1109/icdacai65086.2024.00083.

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Arif, Farrukh, Waleed Ahmed Khan, and Asad-ur-Rehman Khan. "LiDAR-UAV Integrated Digitization of Civil Infrastructure for Visualization of Physical Condition." In Technology Enabled Civil Infrastructure Engineering & Management Conference. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-6boxwp.

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Civil infrastructure is prone to deterioration due to several factors like loading and environmental agents. Condition assessment of these infrastructures is done on a visualization basis by the field inspector. The data collected by the inspector is biased and depends on the perception, experience, and visuals of the inspector. The data collected in terms of images and characteristics of the deterioration is recorded on a qualitative basis in the data log. The report is then presented to the managers or decision-makers to make decisions on the maintenance of the facility. In this era, various

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Youssef, Elbalghiti, Mouna El Mkhalet, and Nouzha Lamdouar. "Application of Artificial Intelligence in the Evaluation and Prediction of the Stability of Civil Engineering Structures: Case Study of the Iminifri Natural Bridge, Demnate, Morocco." In 2025 5th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET). IEEE, 2025. https://doi.org/10.1109/iraset64571.2025.11008136.

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Šváb, Patrik, Patrik Géci, and Sebastián Čikovský. "Harnessing Artificial Intelligence in Civil Aviation." In 2024 New Trends in Aviation Development (NTAD). IEEE, 2024. https://doi.org/10.1109/ntad63796.2024.10850033.

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Islam, Md Zahidul, Chin Jian Leo, Ju Jia Zou, Samanthika Liyanapathirana, and Pan Hu. "Artificial Intelligence in Civil Engineering Education." In International Conference on Advancements in Engineering Education. Science Technology and Management Crescent Australia, 2024. https://doi.org/10.71427/icaeed2025/14.

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Civil engineering is a multifaceted field that involves designing, constructing, and maintaining infrastructure and the built environment. However, there are notable complexities in civil engineering subjects that are challenging to be taught in the classroom. Although dealing with these complexities was once a challenge for engineers trained in traditional classrooms, artificial intelligence (AI) technologies now increasingly transform the contemporary classroom in terms of the curricula and pedagogy to provide a better educational outcome. AI has emerged as a powerful tool in numerous fields

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Coker, L. O. Toriola, N. AYekini, H. Alaka, and A. O. Ajimo. "Artificial Intelligence Systems for Teaching and Learning in Civil Engineering: Conceptual Framework." In 9th International Conference on Artificial Intelligence and Applications (AIAP 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120405.

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Artificial intelligence technology is based on design of machine or computer application that mimic human intelligent. Use of artificial intelligence in teaching and learning in civil engineering is a welcome development. This paper presents a conceptual framework of Artificial Intelligence Systems for Teaching, Learning, and administration of in Civil Engineering education. The proposed system is to be designed using the following tools: Extensible Markup Language (XML) to develop the GUI, Hypertext Pre-processor (PHP) for the web user interface (WUI), APACHE for middleware, MYSQL for databas

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Ouyang, Fan, Pengcheng Jiao, and Amir H. Alavi. "Artificial intelligence-based smart engineering education." In Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, edited by Daniele Zonta and Haiying Huang. SPIE, 2020. http://dx.doi.org/10.1117/12.2557464.

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Kjellgren, Alexander, Per Kettil, Rasmus Rempling, and Mats Karlsson. "Opportunities in Civil Projects with Artificial Intelligence." In IABSE Congress, New Delhi 2023: Engineering for Sustainable Development. International Association for Bridge and Structural Engineering (IABSE), 2023. http://dx.doi.org/10.2749/newdelhi.2023.1207.

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To analyse and compare different production methods, innovative designs and sustainability are essential keys in civil projects. A promising approach is to combine automated design methods supported by artificial intelligence (AI). The purpose of this study was to identify and describe knowledge gaps in this field and necessary method development. A series of interviews were performed with experienced personnel from the construction business in order to point out how evaluation of alternatives in today’s tender processes are performed. Furthermore, a literature review was carried out

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Raporty organizacyjne na temat "Artificial Intelligence in Civil Engineering"

Nadro, Mikailu. Artificial Intelligence in Civil Engineering. ResearchHub Technologies, Inc., 2024. http://dx.doi.org/10.55277/researchhub.a6axlwn6.

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Balali, Vahid. System-of-Systems Integration for Civil Infrastructures Resiliency Toward MultiHazard Events. Mineta Transportation Institute, 2023. http://dx.doi.org/10.31979/mti.2023.2245.

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Civil infrastructure systems—facilities that supply principal services, such as electricity, water, transportation, etc., to a community—are the backbone of modern society. These systems are frequently subject to multi-hazard events, such as earthquakes. The poor resiliency of these infrastructures results in many human casualties and significant economic losses every year. An outline of a holistic view that considers how different civil infrastructure systems operate independently and how they interact and communicate with each other is required to have a resilient infrastructure system. More

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Bhatnagar, Ansh, and Devyani Gajjar. How is artificial intelligence affecting society? Parliamentary Office of Science and Technology, 2024. http://dx.doi.org/10.58248/rr15.

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Bozzo Hauri, Sebastián. The New Frontier of Civil Liability: Artificial Intelligence, Autonomy, and Consumer Protection. Carver University; Universidad Autónoma de Chile, 2025. https://doi.org/10.32457/bozzo2202599.

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Technological evolution has entered a phase that challenges the very foundations of private law. The emergence of systems based on artificial intelligence (AI)—particularly in their most recent form, so-called AI agents—compels a reassessment of the traditional framework of civil liability, especially in the field of consumer law. The trajectory of AI has followed a path marked by three distinct waves. The first wave was predictive AI, trained on historical data to anticipate future behavior, as seen in recommendation engines and segmentation models. The second wave introduced generative AI—su

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Diaz-Herrera, Jorge L. Artificial Intelligence (AI) and Ada: Integrating AI with Mainstream Software Engineering. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada286093.

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Emrich, M., A. Agarwal, B. Jairam, and N. Murthy. Potential Applications of Artificial Intelligence to the Field of Software Engineering. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada216909.

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Mackelprang, Rebecca, Charlie Johnson, and Wilson Sinclair, eds. Security Considerations at the Intersection of Engineering Biology and Artificial Intelligence. Engineering Biology Research Consortium, 2023. http://dx.doi.org/10.25498/e4j017.

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Moskvicheva, Elena. DESIGN AND TECHNOLOGIES WITH ELEMENTS OF ARTIFICIAL INTELLIGENCE. Intellectual Archive, 2025. https://doi.org/10.32370/iaj.3264.

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This article analyzes modern approaches to the development of innovative technical solutions that integrate principles of engineering design, digital technologies, TRIZ methodology, and elements of artificial intelligence. Examples of solutions with a high degree of non-obviousness, protected by patents and implemented in software, are considered

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Daniels, Matthew, Autumn Toney, Melissa Flagg, and Charles Yang. Machine Intelligence for Scientific Discovery and Engineering Invention. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200099.

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The advantages of nations depend in part on their access to new inventions—and modern applications of artificial intelligence can help accelerate the creation of new inventions in the years ahead. This data brief is a first step toward understanding how modern AI and machine learning have begun accelerating growth across a wide array of science and engineering disciplines in recent years.

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Rinuado, Christina, William Leonard, Christopher Morey, Theresa Coumbe, Jaylen Hopson, and Robert Hilborn. Artificial intelligence (AI)–enabled wargaming agent training. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48419.

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Fiscal Year 2021 (FY21) work from the Engineer Research and Development Center Institute for Systems Engineering Research lever-aged deep reinforcement learning to develop intelligent systems (red team agents) capable of exhibiting credible behavior within a military course of action wargaming maritime framework infrastructure. Building from the FY21 research, this research effort sought to explore options to improve upon the wargaming framework infrastructure and to investigate opportunities to improve artificial intelligence (AI) agent behavior. Wargaming framework infrastructure enhancement

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