{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T01:16:18Z","timestamp":1774142178964,"version":"3.50.1"},"reference-count":160,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T00:00:00Z","timestamp":1671148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"DoD Center of Excellence in AI and Machine Learning (CoE-AIML) at the University of Howard","award":["W911NF-20-2-0277"],"award-info":[{"award-number":["W911NF-20-2-0277"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents the findings of detailed and comprehensive technical literature aimed at identifying the current and future research challenges of tactical autonomy. It discusses in great detail the current state-of-the-art powerful artificial intelligence (AI), machine learning (ML), and robot technologies, and their potential for developing safe and robust autonomous systems in the context of future military and defense applications. Additionally, we discuss some of the technical and operational critical challenges that arise when attempting to practically build fully autonomous systems for advanced military and defense applications. Our paper provides the state-of-the-art advanced AI methods available for tactical autonomy. To the best of our knowledge, this is the first work that addresses the important current trends, strategies, critical challenges, tactical complexities, and future research directions of tactical autonomy. We believe this work will greatly interest researchers and scientists from academia and the industry working in the field of robotics and the autonomous systems community. We hope this work encourages researchers across multiple disciplines of AI to explore the broader tactical autonomy domain. We also hope that our work serves as an essential step toward designing advanced AI and ML models with practical implications for real-world military and defense settings.<\/jats:p>","DOI":"10.3390\/s22249916","type":"journal-article","created":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T04:30:00Z","timestamp":1671165000000},"page":"9916","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2014-2749","authenticated-orcid":false,"given":"Desta Haileselassie","family":"Hagos","sequence":"first","affiliation":[{"name":"DoD Center of Excellence in Artificial Intelligence and Machine Learning (CoE-AIML), Howard University, Washington, DC 20059, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3638-3464","authenticated-orcid":false,"given":"Danda B.","family":"Rawat","sequence":"additional","affiliation":[{"name":"DoD Center of Excellence in Artificial Intelligence and Machine Learning (CoE-AIML), Howard University, Washington, DC 20059, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"109969","DOI":"10.1016\/j.paid.2020.109969","article-title":"Evolution and revolution: Personality research for the coming world of robots, artificial intelligence, and autonomous systems","volume":"169","author":"Matthews","year":"2021","journal-title":"Personal. Individ. Differ."},{"key":"ref_2","first-page":"368","article-title":"Autonomous systems","volume":"26","author":"Watson","year":"2005","journal-title":"Johns Hopkins Apl. Tech. Dig."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Franklin, S., and Graesser, A. (1996, January 12\u201313). Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agents. Proceedings of the International Workshop on Agent Theories, Architectures, and Languages, Budapest, Hungary.","DOI":"10.1007\/BFb0013570"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/0921-8890(95)00011-4","article-title":"When are robots intelligent autonomous agents?","volume":"15","author":"Steels","year":"1995","journal-title":"Robot. Auton. Syst."},{"key":"ref_5","first-page":"103","article-title":"Artificial intelligence in cybersecurity","volume":"1","author":"Wirkuttis","year":"2017","journal-title":"Cyber Intell. Secur."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1080\/03088839.2020.1788731","article-title":"Big data and artificial intelligence in the maritime industry: A bibliometric review and future research directions","volume":"47","author":"Munim","year":"2020","journal-title":"Marit. Policy Manag."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"05012","DOI":"10.1051\/itmconf\/20171205012","article-title":"Ship detection and classification on optical remote sensing images using deep learning","volume":"12","author":"Liu","year":"2017","journal-title":"ITM Web Conf. EDP Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"05019003","DOI":"10.1061\/(ASCE)IS.1943-555X.0000477","article-title":"Deep learning for critical infrastructure resilience","volume":"25","author":"Dick","year":"2019","journal-title":"J. Infrastruct. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1504\/IJCIS.2008.017438","article-title":"The state of the art in critical infrastructure protection: A framework for convergence","volume":"4","author":"Bagheri","year":"2008","journal-title":"Int. J. Crit. Infrastruct."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1080\/095281300409801","article-title":"Grounding autonomy adjustment on delegation and trust theory","volume":"12","author":"Falcone","year":"2000","journal-title":"J. Exp. Theor. Artif. Intell."},{"key":"ref_11","unstructured":"Force, U.A. (2013). Autonomy Science and Technology Strategy, US Air Force Research Lab."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1109\/TIV.2019.2955905","article-title":"Combining planning and deep reinforcement learning in tactical decision making for autonomous driving","volume":"5","author":"Hoel","year":"2019","journal-title":"IEEE Trans. Intell. Veh."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kochenderfer, M.J. (2015). Decision Making under Uncertainty: Theory and Application, MIT Press.","DOI":"10.7551\/mitpress\/10187.001.0001"},{"key":"ref_14","first-page":"15","article-title":"Machine ethics: Creating an ethical intelligent agent","volume":"28","author":"Anderson","year":"2007","journal-title":"AI Mag."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"973","DOI":"10.1177\/1461444816676645","article-title":"Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability","volume":"20","author":"Ananny","year":"2018","journal-title":"New Media Soc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"102509","DOI":"10.1016\/j.futures.2019.102509","article-title":"Ethics of quantification or quantification of ethics?","volume":"116","author":"Saltelli","year":"2020","journal-title":"Futures"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/MIS.2006.80","article-title":"The nature, importance, and difficulty of machine ethics","volume":"21","author":"Moor","year":"2006","journal-title":"IEEE Intell. Syst."},{"key":"ref_18","first-page":"27","article-title":"There is no agency without attention","volume":"38","author":"Bello","year":"2017","journal-title":"AI Mag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MIS.2006.76","article-title":"Particularism and the classification and reclassification of moral cases","volume":"21","author":"Guarini","year":"2006","journal-title":"IEEE Intell. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1109\/MIS.2006.67","article-title":"Computational models of ethical reasoning: Challenges, initial steps, and future directions","volume":"21","author":"McLaren","year":"2006","journal-title":"IEEE Intell. Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/MIS.2006.64","article-title":"An approach to computing ethics","volume":"21","author":"Anderson","year":"2006","journal-title":"IEEE Intell. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1109\/MIS.2006.82","article-title":"Toward a general logicist methodology for engineering ethically correct robots","volume":"21","author":"Bringsjord","year":"2006","journal-title":"IEEE Intell. Syst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/MIS.2006.77","article-title":"Prospects for a Kantian machine","volume":"21","author":"Powers","year":"2006","journal-title":"IEEE Intell. Syst."},{"key":"ref_24","unstructured":"Timm, I.J. (2006). Strategic Management of Autonomous Software Systems, TZI-Bericht Center for Computing Technologies, University of Bremen."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Timm, I.J., Knirsch, P., Kreowski, H.J., and Timm-Giel, A. (2007). Autonomy in software systems. Understanding Autonomous Cooperation and Control in Logistics, Springer.","DOI":"10.1007\/978-3-540-47450-0_17"},{"key":"ref_26","unstructured":"Schumann, R., Lattner, A.D., and Timm, I.J. (2008, January 26\u201328). Regulated Autonomy: A Case Study. Proceedings of the Intelligente Systeme zur Entscheidungsunterst\u00fctzung, Teilkonferenz der Multikonferenz Wirtschaftsinformatik, Munich, Germany."},{"key":"ref_27","unstructured":"Shin, K. (2022, November 10). Software Agents Metrics. A Preliminary Study & Development of a Metric Analyzer. Project Report. Number H98010. Available online: https:\/\/scholar.googleusercontent.com\/scholar.bib?q=info:vcxqs0L7Ym4J:scholar.google.com\/&output=citation&scisdr=CgULkJNpEPjG5QHJmH8:AAGBfm0AAAAAY5rPgH8NZ8JRnDPfhR2PtXe_gx42Z-7j&scisig=AAGBfm0AAAAAY5rPgBdJQx3yMsePCK7tRcDAEDwManM9&scisf=4&ct=citation&cd=-1&hl=en."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Haglich, P., Rouff, C., and Pullum, L. (2010, January 20\u201322). Detecting emergence in social networks. Proceedings of the 2010 IEEE Second International Conference on Social Computing, Minneapolis, MN, USA.","DOI":"10.1109\/SocialCom.2010.107"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1080\/13600834.2019.1573501","article-title":"The European Union general data protection regulation: What it is and what it means","volume":"28","author":"Hoofnagle","year":"2019","journal-title":"Inf. Commun. Technol. Law"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Voigt, P., and Von dem Bussche, A. (2017). The EU General Data Protection Regulation (GDPR). A Practical Guide, Springer International Publishing. [1st ed.].","DOI":"10.1007\/978-3-319-57959-7"},{"key":"ref_31","unstructured":"Federal Trade Commission (2022, November 10). Fair Credit Reporting Act, Available online: https:\/\/www.ftc.gov\/legal-library\/browse\/statutes\/fair-credit-reporting-act."},{"key":"ref_32","unstructured":"Russell, S.J., and Norvig, P. (2003). Artificial Intelligence: A Modern Approach, Pearson."},{"key":"ref_33","unstructured":"Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., and Riedmiller, M. (2013). Playing atari with deep reinforcement learning. arXiv."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1038\/nature16961","article-title":"Mastering the game of Go with deep neural networks and tree search","volume":"529","author":"Silver","year":"2016","journal-title":"Nature"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/S0004-3702(01)00129-1","article-title":"Deep Blue","volume":"134","author":"Campbell","year":"2002","journal-title":"Artif. Intell."},{"key":"ref_36","first-page":"59","article-title":"Building Watson: An overview of the DeepQA project","volume":"31","author":"Ferrucci","year":"2010","journal-title":"AI Mag."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1771","DOI":"10.1007\/s11948-020-00213-5","article-title":"How to design AI for social good: Seven essential factors","volume":"26","author":"Floridi","year":"2020","journal-title":"Sci. Eng. Ethics"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Carton, S., Helsby, J., Joseph, K., Mahmud, A., Park, Y., Walsh, J., Cody, C., Patterson, C.E., Haynes, L., and Ghani, R. (2016, January 13\u201317). Identifying police officers at risk of adverse events. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA.","DOI":"10.1145\/2939672.2939698"},{"key":"ref_39","first-page":"184","article-title":"Artificial intelligence as a positive and negative factor in global risk","volume":"1","author":"Yudkowsky","year":"2008","journal-title":"Glob. Catastrophic Risks"},{"key":"ref_40","unstructured":"Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J., and Man\u00e9, D. (2016). Concrete problems in AI safety. arXiv."},{"key":"ref_41","unstructured":"Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies, Oxford University Press."},{"key":"ref_42","unstructured":"Bojarski, M., Del Testa, D., Dworakowski, D., Firner, B., Flepp, B., Goyal, P., Jackel, L.D., Monfort, M., Muller, U., and Zhang, J. (2016). End to end learning for self-driving cars. arXiv."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1109\/MITS.2016.2583491","article-title":"Autonomous vehicle safety: An interdisciplinary challenge","volume":"9","author":"Koopman","year":"2017","journal-title":"IEEE Intell. Transp. Syst. Mag."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Nguyen, A., Nguyen, N., Tran, K., Tjiputra, E., and Tran, Q.D. (2020, January 25\u201329). Autonomous navigation in complex environments with deep multimodal fusion network. Proceedings of the 2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA.","DOI":"10.1109\/IROS45743.2020.9341494"},{"key":"ref_45","unstructured":"Lary, D.J. (2010). Artificial intelligence in Aerospace. Aerospace Technologies Advancements, IntechOpen."},{"key":"ref_46","unstructured":"Krishnan, S., Boroujerdian, B., Faust, A., and Reddi, V.J. (2019). Toward exploring end-to-end learning algorithms for autonomous aerial machines. Algorithms and Architectures for Learning in-the-Loop Systems in Autonomous Flight (ICRA), Edge Computing Lab."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MAES.2021.3070862","article-title":"Space-based global maritime surveillance. Part I: Satellite technologies","volume":"36","author":"Soldi","year":"2021","journal-title":"IEEE Aerosp. Electron. Syst. Mag."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Batalden, B.M., Leikanger, P., and Wide, P. (2017, January 12\u201314). Towards autonomous maritime operations. Proceedings of the 2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), Surabaya, Indonesia.","DOI":"10.1109\/CIVEMSA.2017.7995339"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"4316","DOI":"10.1109\/TITS.2020.3032227","article-title":"Deep learning for safe autonomous driving: Current challenges and future directions","volume":"22","author":"Muhammad","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_51","unstructured":"Huval, B., Wang, T., Tandon, S., Kiske, J., Song, W., Pazhayampallil, J., Andriluka, M., Rajpurkar, P., Migimatsu, T., and Cheng-Yue, R. (2015). An empirical evaluation of deep learning on highway driving. arXiv."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Tram, T., Jansson, A., Gr\u00f6nberg, R., Ali, M., and Sj\u00f6berg, J. (2018, January 4\u20137). Learning negotiating behavior between cars in intersections using deep q-learning. Proceedings of the 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, USA.","DOI":"10.1109\/ITSC.2018.8569316"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3065386","article-title":"Imagenet classification with deep convolutional neural networks","volume":"60","author":"Krizhevsky","year":"2017","journal-title":"Commun. ACM"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2806","DOI":"10.1109\/TPAMI.2020.3045007","article-title":"A review on deep learning techniques for video prediction","volume":"44","author":"Oprea","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Hoel, C.J., Wolff, K., and Laine, L. (2018, January 4\u20137). Automated speed and lane change decision making using deep reinforcement learning. Proceedings of the 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, USA.","DOI":"10.1109\/ITSC.2018.8569568"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1109\/TITS.2020.3012034","article-title":"Deep learning-based vehicle behavior prediction for autonomous driving applications: A review","volume":"23","author":"Mozaffari","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"102021","DOI":"10.1109\/ACCESS.2019.2926040","article-title":"MIT advanced vehicle technology study: Large-scale naturalistic driving study of driver behavior and interaction with automation","volume":"7","author":"Fridman","year":"2019","journal-title":"IEEE Access"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Gurghian, A., Koduri, T., Bailur, S.V., Carey, K.J., and Murali, V.N. (2016, January 27\u201330). Deeplanes: End-to-end lane position estimation using deep neural networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, Las Vegas, NV, USA.","DOI":"10.1109\/CVPRW.2016.12"},{"key":"ref_59","unstructured":"Sutton, R.S., and Barto, A.G. (2018). Reinforcement Learning: An Introduction, MIT Press."},{"key":"ref_60","unstructured":"Grudic, G.Z., Kumar, V., and Ungar, L. (2003, January 27\u201331). Using policy gradient reinforcement learning on autonomous robot controllers. Proceedings of the 2003 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No. 03CH37453), Las Vegas, NV, USA."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"6569","DOI":"10.1109\/LRA.2021.3093551","article-title":"A sim-to-real pipeline for deep reinforcement learning for autonomous robot navigation in cluttered rough terrain","volume":"6","author":"Hu","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_62","unstructured":"Shalev-Shwartz, S., Shammah, S., and Shashua, A. (2016). Safe, multi-agent, reinforcement learning for autonomous driving. arXiv."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Branavan, S.R., Chen, H., Zettlemoyer, L., and Barzilay, R. (2009, January 2\u20137). Reinforcement learning for mapping instructions to actions. Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, Singapore.","DOI":"10.3115\/1687878.1687892"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Luketina, J., Nardelli, N., Farquhar, G., Foerster, J., Andreas, J., Grefenstette, E., Whiteson, S., and Rockt\u00e4schel, T. (2019). A survey of reinforcement learning informed by natural language. arXiv.","DOI":"10.24963\/ijcai.2019\/880"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1038\/nature24270","article-title":"Mastering the Game of Go without Human Knowledge","volume":"550","author":"Silver","year":"2017","journal-title":"Nature"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1038\/nature14236","article-title":"Human-level control through deep reinforcement learning","volume":"518","author":"Mnih","year":"2015","journal-title":"Nature"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Hoel, C.J., Wolff, K., and Laine, L. (November, January 19). Tactical decision-making in autonomous driving by reinforcement learning with uncertainty estimation. Proceedings of the 2020 IEEE Intelligent Vehicles Symposium (IV), Las Vegas, NV, USA.","DOI":"10.1109\/IV47402.2020.9304614"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Zhang, J., Springenberg, J.T., Boedecker, J., and Burgard, W. (2017, January 24\u201328). Deep reinforcement learning with successor features for navigation across similar environments. Proceedings of the 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada.","DOI":"10.1109\/IROS.2017.8206049"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Matari\u0107, M.J. (1997). Reinforcement learning in the multi-robot domain. Robot Colonies, Springer.","DOI":"10.1007\/978-1-4757-6451-2_4"},{"key":"ref_70","first-page":"1","article-title":"Large scale distributed deep networks","volume":"25","author":"Dean","year":"2012","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_71","unstructured":"Kone\u010dn\u1ef3, J., McMahan, H.B., Ramage, D., and Richt\u00e1rik, P. (2016). Federated optimization: Distributed machine learning for on-device intelligence. arXiv."},{"key":"ref_72","unstructured":"McMahan, B., and Ramage, D. (2017). Federated Learning: Collaborative Machine Learning without Centralized Training Data. Google Res. Blog, 3, Available online: https:\/\/ai.googleblog.com\/2017\/04\/federated-learning-collaborative.html."},{"key":"ref_73","first-page":"374","article-title":"Towards federated learning at scale: System design","volume":"1","author":"Bonawitz","year":"2019","journal-title":"Proc. Mach. Learn. Syst."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Shokri, R., and Shmatikov, V. (2015, January 12\u201316). Privacy-preserving deep learning. Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, Denver, CO, USA.","DOI":"10.1145\/2810103.2813687"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1109\/MCOM.001.2000200","article-title":"Opportunities of federated learning in connected, cooperative, and automated industrial systems","volume":"59","author":"Savazzi","year":"2021","journal-title":"IEEE Commun. Mag."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"10407","DOI":"10.1109\/TWC.2022.3183996","article-title":"Federated Learning on the Road Autonomous Controller Design for Connected and Autonomous Vehicles","volume":"21","author":"Zeng","year":"2022","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"6279","DOI":"10.1109\/TVT.2021.3081049","article-title":"Classifying UAVs with proprietary waveforms via preamble feature extraction and federated learning","volume":"70","author":"Chowdhury","year":"2021","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Levinson, J., Askeland, J., Becker, J., Dolson, J., Held, D., Kammel, S., Kolter, J.Z., Langer, D., Pink, O., and Pratt, V. (2011, January 5\u20139). Towards fully autonomous driving: Systems and algorithms. Proceedings of the 2011 IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, Germany.","DOI":"10.1109\/IVS.2011.5940562"},{"key":"ref_79","unstructured":"Ramsundar, B., Kearnes, S., Riley, P., Webster, D., Konerding, D., and Pande, V. (2015). Massively multitask networks for drug discovery. arXiv."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1126\/science.1259439","article-title":"Amplify scientific discovery with artificial intelligence","volume":"346","author":"Gil","year":"2014","journal-title":"Science"},{"key":"ref_81","unstructured":"Future of Life Institute (2015). Autonomous Weapons: An Open Letter from AI & Robotics Researchers, Future of Life Institute."},{"key":"ref_82","unstructured":"Selbst, A., and Powles, J. (2018, January 23\u201324). \u201cMeaningful Information\u201d and the Right to Explanation. Proceedings of the Conference on Fairness, Accountability and Transparency, New York, NY, USA."},{"key":"ref_83","first-page":"50","article-title":"European Union regulations on algorithmic decision-making and a \u201cright to explanation\u201d","volume":"38","author":"Goodman","year":"2017","journal-title":"AI Mag."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1093\/idpl\/ipx005","article-title":"Why a right to explanation of automated decision-making does not exist in the general data protection regulation","volume":"7","author":"Wachter","year":"2017","journal-title":"Int. Data Priv. Law"},{"key":"ref_85","unstructured":"Samek, W., Wiegand, T., and M\u00fcller, K.R. (2017). Explainable artificial intelligence: Understanding, visualizing and interpreting deep learning models. arXiv."},{"key":"ref_86","unstructured":"Doshi-Velez, F., and Kim, B. (2017). Towards A Rigorous Science of Interpretable Machine Learning. arXiv."},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Gilpin, L.H., Bau, D., Yuan, B.Z., Bajwa, A., Specter, M., and Kagal, L. (2018, January 1\u20134). Explaining explanations: An overview of interpretability of machine learning. Proceedings of the 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA), Turin, Italy.","DOI":"10.1109\/DSAA.2018.00018"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1089\/big.2016.0051","article-title":"On the safety of machine learning: Cyber-physical systems, decision sciences, and data products","volume":"5","author":"Varshney","year":"2017","journal-title":"Big Data"},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Bostrom, N., and Yudkowsky, E. (2018). The ethics of artificial intelligence. Artificial Intelligence Safety and Security, Chapman and Hall\/CRC.","DOI":"10.1201\/9781351251389-4"},{"key":"ref_90","first-page":"20180085","article-title":"Ethical governance is essential to building trust in robotics and artificial intelligence systems","volume":"376","author":"Winfield","year":"2018","journal-title":"Philos. Trans. R. Soc. Math. Phys. Eng. Sci."},{"key":"ref_91","first-page":"20180081","article-title":"Soft ethics, the governance of the digital and the General Data Protection Regulation","volume":"376","author":"Floridi","year":"2018","journal-title":"Philos. Trans. R. Soc. Math. Phys. Eng. Sci."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"eaan6080","DOI":"10.1126\/scirobotics.aan6080","article-title":"Transparent, explainable, and accountable AI for robotics","volume":"2","author":"Wachter","year":"2017","journal-title":"Sci. Robot."},{"key":"ref_93","first-page":"20180083","article-title":"Algorithms that remember: Model inversion attacks and data protection law","volume":"376","author":"Veale","year":"2018","journal-title":"Philos. Trans. R. Soc. Math. Phys. Eng. Sci."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/MSP.2018.2701152","article-title":"Enslaving the algorithm: From a \u201cright to an explanation\u201d to a \u201cright to better decisions\u201d?","volume":"16","author":"Edwards","year":"2018","journal-title":"IEEE Secur. Priv."},{"key":"ref_95","doi-asserted-by":"crossref","unstructured":"Liao, Q.V., Gruen, D., and Miller, S. (2020, January 25\u201330). Questioning the AI: Informing design practices for explainable AI user experiences. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA.","DOI":"10.1145\/3313831.3376590"},{"key":"ref_96","first-page":"1","article-title":"A survey of methods for explaining black box models","volume":"51","author":"Guidotti","year":"2018","journal-title":"Acm Comput. Surv. CSUR"},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1515\/popets-2015-0007","article-title":"Automated Experiments on Ad Privacy Settings","volume":"2015","author":"Datta","year":"2015","journal-title":"Proc. Priv. Enhancing Technol."},{"key":"ref_98","first-page":"1","article-title":"Alibi Explain: Algorithms for Explaining Machine Learning Models","volume":"22","author":"Klaise","year":"2021","journal-title":"J. Mach. Learn. Res."},{"key":"ref_99","unstructured":"Arya, V., Bellamy, R.K., Chen, P.Y., Dhurandhar, A., Hind, M., Hoffman, S.C., Houde, S., Liao, Q.V., Luss, R., and Mojsilovi\u0107, A. (2019). One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques. arXiv."},{"key":"ref_100","unstructured":"Biecek, P. (2022, December 14). DALEX2: Descriptive Machine Learning Explanations. Available online: https:\/\/github.com\/ModelOriented\/DALEX2."},{"key":"ref_101","first-page":"1","article-title":"DALEX: Explainers for Complex Predictive Models in R","volume":"19","author":"Biecek","year":"2018","journal-title":"J. Mach. Learn. Res."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1145\/3313109","article-title":"Trustworthy machine learning and artificial intelligence","volume":"25","author":"Varshney","year":"2019","journal-title":"XRDS Crossroads Acm Mag. Stud."},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cpet.2021.09.007","article-title":"Trustworthy Artificial Intelligence in Medical Imaging","volume":"17","author":"Hasani","year":"2022","journal-title":"PET Clin."},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Papernot, N., McDaniel, P., Goodfellow, I., Jha, S., Celik, Z.B., and Swami, A. (2016). Practical black-box attacks against deep learning systems using adversarial examples. arXiv.","DOI":"10.1145\/3052973.3053009"},{"key":"ref_105","unstructured":"Ji, Z., Lipton, Z.C., and Elkan, C. (2014). Differential privacy and machine learning: A survey and review. arXiv."},{"key":"ref_106","unstructured":"Adebayo, J., Kagal, L., and Pentland, A. (2015, January 26\u201329). The hidden cost of efficiency: Fairness and discrimination in predictive modeling. Proceedings of the Bloomberg Data for Good Exchange Conference, Madrid, Spain."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1007\/s11023-018-9482-5","article-title":"AI4People\u2014An Ethical Framework for a Good AI society: Opportunities, Risks, Principles, and Recommendations","volume":"28","author":"Floridi","year":"2018","journal-title":"Minds Mach."},{"key":"ref_108","unstructured":"Kaur, D., Uslu, S., and Durresi, A. (September, January 31). Requirements for trustworthy artificial intelligence\u2014A review. Proceedings of the International Conference on Network-Based Information Systems, Victoria, BC, Canada."},{"key":"ref_109","first-page":"27","article-title":"Autonomy in space: Current capabilities and future challenge","volume":"28","author":"Morris","year":"2007","journal-title":"AI Mag."},{"key":"ref_110","unstructured":"Charlton, P., Bonnefoy, D., and Lhuillier, N. (June, January 28). Dealing with interoperability for agent-based services. Proceedings of the Fifth International Conference on Autonomous Agents, Montreal, QC, Canada."},{"key":"ref_111","unstructured":"Kopetz, H., and Sytems, R.T. (1997). Design principles for distributed embedded applications. Real-Time Systems, Springer."},{"key":"ref_112","first-page":"1","article-title":"Metrics for software adaptability","volume":"158","author":"Subramanian","year":"2001","journal-title":"Proc. Softw. Qual. Manag. (SQM 2001)"},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1037\/amp0000241","article-title":"Foundations of teamwork and collaboration","volume":"73","author":"Driskell","year":"2018","journal-title":"Am. Psychol."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"103174","DOI":"10.1016\/j.im.2019.103174","article-title":"Machines as teammates: A research agenda on AI in team collaboration","volume":"57","author":"Seeber","year":"2020","journal-title":"Inf. Manag."},{"key":"ref_115","unstructured":"Sukthankar, G., Shumaker, R., and Lewis, M. (2013). Intelligent Agents as Teammates. Theories of Team Cognition, Routledge."},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1109\/THMS.2013.2293535","article-title":"Human\u2013agent teaming for multirobot control: A review of human factors issues","volume":"44","author":"Chen","year":"2014","journal-title":"IEEE Trans.-Hum.-Mach. Syst."},{"key":"ref_117","unstructured":"McDermott, P., Dominguez, C., Kasdaglis, N., Ryan, M., Trhan, I., and Nelson, A. (2018). Human\u2013Machine Teaming Systems Engineering Guide, MITRE CORP. Technical Report."},{"key":"ref_118","first-page":"1","article-title":"Designing AI systems with human\u2013machine teams","volume":"61","author":"Saenz","year":"2020","journal-title":"MIT Sloan Manag. Rev."},{"key":"ref_119","doi-asserted-by":"crossref","unstructured":"Davenport, T.H. (2018). The AI Advantage: How to Put the Artificial Intelligence Revolution to Work, MIT Press.","DOI":"10.7551\/mitpress\/11781.001.0001"},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1038\/s41746-022-00597-7","article-title":"Human\u2013machine teaming is key to AI adoption: Clinicians\u2019 experiences with a deployed machine learning system","volume":"5","author":"Henry","year":"2022","journal-title":"NPJ Digit. Med."},{"key":"ref_121","first-page":"610","article-title":"The Utility of Explainable AI in Ad Hoc Human\u2013Machine Teaming","volume":"34","author":"Paleja","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_122","unstructured":"Russell, S.J. (2010). Artificial Intelligence a Modern Approach, Pearson Education Inc."},{"key":"ref_123","unstructured":"Smith, C.J. (2019). Designing trustworthy AI: A human\u2013machine teaming framework to guide development. arXiv."},{"key":"ref_124","doi-asserted-by":"crossref","unstructured":"Wang, D., Churchill, E., Maes, P., Fan, X., Shneiderman, B., Shi, Y., and Wang, Q. (2020, January 25\u201330). From human-human collaboration to Human-AI collaboration: Designing AI systems that can work together with people. Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA.","DOI":"10.1145\/3334480.3381069"},{"key":"ref_125","doi-asserted-by":"crossref","unstructured":"Miller, B., Hasbrouck, S., and Udrea, B. (2021, January 15\u201317). Development of Human\u2013Machine Collaborative Systems through Use of Observe-Orient-Decide-Act (OODA) Loop. Proceedings of the ASCEND 2021, Virtual.","DOI":"10.2514\/6.2021-4092"},{"key":"ref_126","doi-asserted-by":"crossref","unstructured":"Andriluka, M., Uijlings, J.R., and Ferrari, V. (2018, January 22\u201326). Fluid annotation: A human\u2013machine collaboration interface for full image annotation. Proceedings of the 26th ACM International Conference on Multimedia, Seoul, Republic of Korea.","DOI":"10.1145\/3240508.3241916"},{"key":"ref_127","first-page":"1","article-title":"An approach to human\u2013machine collaboration in innovation","volume":"32","author":"McCaffrey","year":"2018","journal-title":"AI EDAM"},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3338243","article-title":"Human\u2013Machine Collaboration for Content Regulation: The Case of Reddit Automoderator","volume":"26","author":"Jhaver","year":"2019","journal-title":"ACM Trans.-Comput.-Hum. Interact. TOCHI"},{"key":"ref_129","doi-asserted-by":"crossref","unstructured":"Russakovsky, O., Li, L.J., and Fei-Fei, L. (2015, January 7\u201312). Best of both worlds: Human\u2013machine collaboration for object annotation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298824"},{"key":"ref_130","doi-asserted-by":"crossref","unstructured":"Stone, P., Kaminka, G.A., Kraus, S., and Rosenschein, J.S. (2010, January 11\u201315). Ad hoc autonomous agent teams: Collaboration without pre-coordination. Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, Atlanta, GA, USA.","DOI":"10.1609\/aaai.v24i1.7529"},{"key":"ref_131","unstructured":"Stone, P., and Kraus, S. (2010, January 10\u201314). To teach or not to teach?: Decision making under uncertainty in ad hoc teams. Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, ON, Canada."},{"key":"ref_132","unstructured":"Wu, F., Zilberstein, S., and Chen, X. (2011, January 16\u201322). Online planning for ad hoc autonomous agent teams. Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, Barcelona, Spain."},{"key":"ref_133","doi-asserted-by":"crossref","unstructured":"Lewis, M., Sycara, K., and Walker, P. (2018). The role of trust in human-robot interaction. Foundations of Trusted Autonomy, Springer.","DOI":"10.1007\/978-3-319-64816-3_8"},{"key":"ref_134","doi-asserted-by":"crossref","unstructured":"Salas, E., Goodwin, G.F., and Burke, C.S. (2008). Team Effectiveness in Complex Organizations: Cross-Disciplinary Perspectives and Approaches, Routledge.","DOI":"10.4324\/9780203889312"},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1080\/1463922X.2017.1315750","article-title":"Situation awareness-based agent transparency and human-autonomy teaming effectiveness","volume":"19","author":"Chen","year":"2018","journal-title":"Theor. Issues Ergon. Sci."},{"key":"ref_136","doi-asserted-by":"crossref","unstructured":"Lyons, J.B., and Havig, P.R. (2014, January 22\u201327). Transparency in a human\u2013machine context: Approaches for fostering shared awareness\/intent. Proceedings of the International Conference on Virtual, Augmented and Mixed Reality, Virtual.","DOI":"10.1007\/978-3-319-07458-0_18"},{"key":"ref_137","doi-asserted-by":"crossref","unstructured":"Chen, J.Y., Procci, K., Boyce, M., Wright, J.L., Garcia, A., and Barnes, M. (2014). Situation Awareness-Based Agent Transparency, Army Research Lab. Technical Report.","DOI":"10.21236\/ADA600351"},{"key":"ref_138","doi-asserted-by":"crossref","unstructured":"Sanneman, L., and Shah, J.A. (2020, January 9\u201313). A situation awareness-based framework for design and evaluation of explainable AI. Proceedings of the International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, Auckland, New Zealand.","DOI":"10.1007\/978-3-030-51924-7_6"},{"key":"ref_139","doi-asserted-by":"crossref","unstructured":"Malone, T.W., and Crowston, K. (1990, January 7\u201310). What is coordination theory and how can it help design cooperative work systems?. Proceedings of the 1990 ACM Conference on Computer-Supported Cooperative Work, Los Angeles, CA, USA.","DOI":"10.1145\/99332.99367"},{"key":"ref_140","doi-asserted-by":"crossref","unstructured":"Salas, E., Rosen, M.A., Burke, C.S., and Goodwin, G.F. (2008). The wisdom of collectives in organizations: An update of the teamwork competencies. Team Effectiveness in Complex Organizations, Routledge.","DOI":"10.4324\/9780203889312-11"},{"key":"ref_141","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1002\/0471739448.ch6","article-title":"Common ground and coordination in joint activity","volume":"53","author":"Klein","year":"2005","journal-title":"Organ. Simul."},{"key":"ref_142","doi-asserted-by":"crossref","unstructured":"Christoffersen, K., and Woods, D.D. (2002). How to make automated systems team players. Advances in Human Performance and Cognitive Engineering Research, Emerald Group Publishing Limited.","DOI":"10.1016\/S1479-3601(02)02003-9"},{"key":"ref_143","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1006\/jesp.1996.0006","article-title":"Tacit coordination in anticipation of small group task completion","volume":"32","author":"Wittenbaum","year":"1996","journal-title":"J. Exp. Soc. Psychol."},{"key":"ref_144","doi-asserted-by":"crossref","first-page":"163","DOI":"10.5465\/amr.2008.27751276","article-title":"Team implicit coordination processes: A team knowledge\u2013based approach","volume":"33","author":"Rico","year":"2008","journal-title":"Acad. Manag. Rev."},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1108\/TPM-03-2020-0024","article-title":"Team implicit coordination based on transactive memory systems","volume":"26","author":"Nawata","year":"2020","journal-title":"Team Perform. Manag. Int. J."},{"key":"ref_146","doi-asserted-by":"crossref","unstructured":"MacMillan, J., Entin, E.E., and Serfaty, D. (2004). Communication Overhead: The Hidden Cost of Team Cognition. Team Cognition: Understanding the Factors That Drive Process and Performance, American Psychological Association.","DOI":"10.1037\/10690-004"},{"key":"ref_147","unstructured":"Miller, C.A., Funk, H., Goldman, R., Meisner, J., and Wu, P. (2005, January 22\u201327). Implications of adaptive vs. adaptable UIs on decision making: Why \u201cautomated adaptiveness\u201d is not always the right answer. Proceedings of the 1st International Conference on Augmented Cognition, Las Vegas, NV, USA."},{"key":"ref_148","doi-asserted-by":"crossref","unstructured":"Truong, T.C., Zelinka, I., Plucar, J., \u010cand\u00edk, M., and \u0160ulc, V. (2020). Artificial intelligence and cybersecurity: Past, presence, and future. Artificial Intelligence and Evolutionary Computations in Engineering Systems, Springer.","DOI":"10.1007\/978-981-15-0199-9_30"},{"key":"ref_149","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1038\/s42256-019-0109-1","article-title":"Trusting artificial intelligence in cybersecurity is a double-edged sword","volume":"1","author":"Taddeo","year":"2019","journal-title":"Nat. Mach. Intell."},{"key":"ref_150","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/s11023-019-09504-8","article-title":"Three ethical challenges of applications of artificial intelligence in cybersecurity","volume":"29","author":"Taddeo","year":"2019","journal-title":"Minds Mach."},{"key":"ref_151","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/65.283931","article-title":"Network intrusion detection","volume":"8","author":"Mukherjee","year":"1994","journal-title":"IEEE Netw."},{"key":"ref_152","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/0167-4048(93)90110-Q","article-title":"NADIR: An automated system for detecting network intrusion and misuse","volume":"12","author":"Hochberg","year":"1993","journal-title":"Comput. Secur."},{"key":"ref_153","doi-asserted-by":"crossref","first-page":"2435","DOI":"10.1016\/S1389-1286(99)00112-7","article-title":"Bro: A system for detecting network intruders in real-time","volume":"31","author":"Paxson","year":"1999","journal-title":"Comput. Netw."},{"key":"ref_154","unstructured":"Hu, W., Liao, Y., and Vemuri, V.R. (2003, January 23\u201324). Robust Support Vector Machines for Anomaly Detection in Computer Security. Proceedings of the ICMLA, Los Angeles, CA, USA."},{"key":"ref_155","unstructured":"Ghosh, A.K., Wanken, J., and Charron, F. (1998, January 7\u201311). Detecting anomalous and unknown intrusions against programs. Proceedings of the 14th Annual Computer Security Applications Conference (Cat. No. 98Ex217), Phoenix, AZ, USA."},{"key":"ref_156","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1145\/322510.322526","article-title":"Temporal sequence learning and data reduction for anomaly detection","volume":"2","author":"Lane","year":"1999","journal-title":"Acm Trans. Inf. Syst. Secur. TISSEC"},{"key":"ref_157","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1016\/S1389-1286(00)00136-5","article-title":"Intrusion detection using autonomous agents","volume":"34","author":"Spafford","year":"2000","journal-title":"Comput. Netw."},{"key":"ref_158","doi-asserted-by":"crossref","first-page":"107784","DOI":"10.1016\/j.compeleceng.2022.107784","article-title":"Artificial intelligence for intrusion detection systems in unmanned aerial vehicles","volume":"99","author":"Whelan","year":"2022","journal-title":"Comput. Electr. Eng."},{"key":"ref_159","doi-asserted-by":"crossref","unstructured":"Cardenas, A.A., Amin, S., and Sastry, S. (2008, January 17\u201320). Secure control: Towards survivable cyber-physical systems. Proceedings of the 28th International Conference on Distributed Computing Systems Workshops, Beijing, China.","DOI":"10.1109\/ICDCS.Workshops.2008.40"},{"key":"ref_160","doi-asserted-by":"crossref","unstructured":"Straub, J., McMillan, J., Yaniero, B., Schumacher, M., Almosalami, A., Boatey, K., and Hartman, J. (2017, January 18\u201321). CyberSecurity considerations for an interconnected self-driving car system of systems. Proceedings of the 2017 12th System of Systems Engineering Conference (SoSE), Waikoloa, HI, USA.","DOI":"10.1109\/SYSOSE.2017.7994973"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/24\/9916\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:42:35Z","timestamp":1760146955000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/24\/9916"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,16]]},"references-count":160,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["s22249916"],"URL":"https:\/\/doi.org\/10.3390\/s22249916","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,16]]}}}