Welcome to Brainless Intelligence blog! This is the final blog which covers the Military sector and in here it will be discussed the Artificial Intelligence in Simulation. Artificial Intelligence is a disruptive technology that can conduct various cognitive processes such as learning, processing, decision making, forecasting, self-correction, and making judgments based on simulated drivers. Artificial intelligence allows for the development of intelligent functions that can process, evaluate, develop, and interact with other systems. Artificial intelligence using algorithms improves the ability to retrieve past knowledge and analyse them to forecast future actions. Artificial Intelligence is becoming increasingly significant and helpful in military simulation training and deployment tasks. The primary characteristics of simulation are that it works well in challenging and complex situations. The tasks are appraised more intelligently with the help of simulation. Soldiers may devise possible solutions, test processes, tactics, and resources, allowing them to be prepared for a realistic scenario and respond quickly to any actions (Huang et al., 2020). Image Source: https://www.army.mil/article/19599/simulators_always_valuable_in_military_training (Chang, 2009). Artificial Intelligence and Machine Learning are used to personalise army training simulations. The data generated after each training will be analysed and utilised as an insightful tool for analytics, allowing them to develop new methods, decisions, and strategies for real-world operations. Artificial Intelligence feedback may aid in the refinement and formation of approaches and in identifying right practices. Machine learning adjusts the employed behaviour and changes strategies in different simulations throughout simulation training (Svenmark et al., 2018). Image Source: https://www.flickr.com/photos/187794252@N03/50809568208 (Huang, 2020). The military decision-making process is a critical aspect, and by incorporating Artificial Intelligence into simulations, this process may be applied and analysed more precisely. Pattern recognition, assisting in processing vast amounts of data, detecting persons in pictures, and observation in data streams are all examples of sensory modes that Artificial Intelligence technologies may employ. Artificial intelligence in simulation allows for a better knowledge of the operating environment. This can reveal the opponent's intents and unobservable characteristics, allowing for modifications in strategy. Plan creation can aid in developing policies and objectives that must be met or avoided. Artificial Intelligence simulations can give assurance about the existing condition or forecast future developments. Artificial Intelligence in simulation gives an in-depth knowledge of the operational environment and decision-making process, which may be employed in real-world operations to respond rapidly while maintaining tactical and logical responses. The soldier would gain a good grasp of the surroundings, and the observation would be swift and invisible to the opponent, which Artificial Intelligence in Simulation aims to deliver (Kerbusch, Bas and Smit, 2018). Image Source: https://www.businessinsider.com/army-special-forces-practice-conventional-unconventional-warfare-2019-10?r=US&IR=T (Orcutt, 2019). The main goal of employing simulation in the military is to develop a method for quickly deploying a behavioural model and using the data collected to enhance parametric, resulting in reinforced learning (Stein and Gonzalez, 2011). Simulations guided by Artificial Intelligence can give high-quality findings and be capable of processing and analysing enormous amounts of data simultaneously and adapting tactics and behaviours to get the best possible outcomes for military goals and development (Roessingh et al., 2017). Artificial Intelligence feedback is given to ensure that the data is not disregarded. Artificial Intelligence identifies and restricts the sharing of Simulation outcomes, allowing only a select group of people to view the data and modify future simulations of strategic and tactical growth (Roessingh et al., 2017). Stay tuned for the very last blog to be released this week, which covers more interesting information about AI in Military! References:Chang, P. (2009). 'Simulators always valuable in military training'. Available at: https://www.army.mil/article/19599/simulators_always_valuable_in_military_training [Accessed: 28 March 2022].
Huang, V. (2020). 'Military virtual simulation training mockup psd army technology'. Available at: https://www.flickr.com/photos/187794252@N03/50809568208 [Accessed: 28 March 2022]. Huang, S., Li, S., Meng, S., Wu, W., Wang, H., Su, K. and Peng, R. (2020). ‘Research on simulation training method based on computer simulation technology.’, Journal of Physics, 1676, (1). doi:10.1088/1742-6596/1676/1/012192 Kerbusch, P., Bas, K., Smit, S. (2018). ‘Roles of AI Simulation for Military Decision Making’. Available at: https://www.semanticscholar.org/paper/Roles-of-AI-and-Simulation-for-Military-Decision-Kerbusch/885b182170db541d48ca7f0380bc0447ce56c9ae [Accessed: 27 March 2022]. Orcutt, P. (2019). 'Army Special Forces soldiers teamed up with European troops to practice fighting behind enemy lines'. Available at: https://www.businessinsider.com/army-special-forces-practice-conventional-unconventional-warfare-2019-10?r=US&IR=T [Accessed: 28 March 2022]. Roessingh, J, J., Toubman, A., Oijen, J., Poppinga, G., Amilde, R., Hou, M., Loutsinen, L. (2017), ‘Machine learning techniques for autonomous agents in military simulations.’, pp. 3445-3450. doi: 10.1109/SMC.2017.8123163. Svenmark, P., Luotsinen, L., Nilsson, M., Schubert, J. (2018). ‘Possibilities and challenges for artificial intelligence in military applications.’ In Proceedings of the NATO Big Data and Artificial Intelligence for Military Decision-Making Specialists, pp. 1 – 16. Available at: https://www.researchgate.net/profile/Johan-Schubert/publication/326774966_Possibilities_and_Challenges_for_Artificial_Intelligence_in_Military_Applications/links/5b62d8140f7e9bc79a75979c/Possibilities-and-Challenges-for-Artificial-Intelligence-in-Military-Applications.pdf [Accessed: 28 March 2022]. Stein, G., Gonzalez, A, J. (2011). ‘Building High-Performing Human-Like Tactical Agents Through Observations and Experience.’, Transactions on Systems, Man and Cybernetics. 41, pp. 3. doi: 10.1109/TSMCB.2010.2091955
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