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Advances in Artificial Intelligence ...
~
Tinetti, Fernando G.
Advances in Artificial Intelligence and Applied Cognitive Computing = Proceedings from ICAI’20 and ACC’20 /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Advances in Artificial Intelligence and Applied Cognitive Computing/ edited by Hamid R. Arabnia, Ken Ferens, David de la Fuente, Elena B. Kozerenko, José Angel Olivas Varela, Fernando G. Tinetti.
其他題名:
Proceedings from ICAI’20 and ACC’20 /
其他作者:
Tinetti, Fernando G.
面頁冊數:
XXI, 1184 p. 150 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Cyber-physical systems, IoT. -
電子資源:
https://doi.org/10.1007/978-3-030-70296-0
ISBN:
9783030702960
Advances in Artificial Intelligence and Applied Cognitive Computing = Proceedings from ICAI’20 and ACC’20 /
Advances in Artificial Intelligence and Applied Cognitive Computing
Proceedings from ICAI’20 and ACC’20 /[electronic resource] :edited by Hamid R. Arabnia, Ken Ferens, David de la Fuente, Elena B. Kozerenko, José Angel Olivas Varela, Fernando G. Tinetti. - 1st ed. 2021. - XXI, 1184 p. 150 illus. in color.online resource. - Transactions on Computational Science and Computational Intelligence,2569-7080. - Transactions on Computational Science and Computational Intelligence,.
Introduction -- PART I: ICAI’20 -- Brain models, Brain mapping, Cognitive science -- Natural language processing -- Fuzzy logic and soft computing -- Social impact of AI -- Emerging technologies -- Statistical learning theory -- Unsupervised and Supervised Learning -- Multivariate analysis -- Hierarchical learning models -- Relational learning models -- Bayesian methods -- Meta learning -- Stochastic optimization -- Heuristic optimization techniques -- Neural networks and variations -- Reinforcement learning -- PART II: ACC 2020 -- Novel Computationally Intelligent algorithms -- Bio Inspired Cognitive Algorithms -- Improving Cognition in machine learning systems -- Modeling Human Brain processing systems -- Multimodal learning systems -- Autonomous learning systems -- Reinforced learning -- Conclusion.
The book presents the proceedings of two conferences: The 22nd International Conference on Artificial Intelligence (ICAI’20) and The 4th International Conference on Applied Cognitive Computing (ACC’20). The conferences took place in Las Vegas, NV, USA, July 27-30, 2020, and are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Topics include: deep learning; neural networks; brain models; cognitive science; natural language processing; fuzzy logic and soft computing (ICAI) and novel computationally intelligent algorithms; bio inspired cognitive algorithms; modeling human brain processing systems (ACC); and more. Authors include academics, researchers, and professionals. Presents the proceedings of two conferences as part of the 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20); Includes the tracks: artificial intelligence and applied cognitive computing; Features papers from the 22nd International Conference on AI (ICAI’20) and the 4th International Conference on Applied Cognitive Computing (ACC’20).
ISBN: 9783030702960
Standard No.: 10.1007/978-3-030-70296-0doiSubjects--Topical Terms:
1226036
Cyber-physical systems, IoT.
LC Class. No.: TK1-9971
Dewey Class. No.: 621.382
Advances in Artificial Intelligence and Applied Cognitive Computing = Proceedings from ICAI’20 and ACC’20 /
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Introduction -- PART I: ICAI’20 -- Brain models, Brain mapping, Cognitive science -- Natural language processing -- Fuzzy logic and soft computing -- Social impact of AI -- Emerging technologies -- Statistical learning theory -- Unsupervised and Supervised Learning -- Multivariate analysis -- Hierarchical learning models -- Relational learning models -- Bayesian methods -- Meta learning -- Stochastic optimization -- Heuristic optimization techniques -- Neural networks and variations -- Reinforcement learning -- PART II: ACC 2020 -- Novel Computationally Intelligent algorithms -- Bio Inspired Cognitive Algorithms -- Improving Cognition in machine learning systems -- Modeling Human Brain processing systems -- Multimodal learning systems -- Autonomous learning systems -- Reinforced learning -- Conclusion.
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