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Titlebook: Artificial Intelligence; 17th Russian Confere Sergei O. Kuznetsov,Aleksandr I. Panov Conference proceedings 2019 Springer Nature Switzerlan

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發(fā)表于 2025-3-21 18:43:52 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Artificial Intelligence
期刊簡(jiǎn)稱17th Russian Confere
影響因子2023Sergei O. Kuznetsov,Aleksandr I. Panov
視頻videohttp://file.papertrans.cn/163/162067/162067.mp4
學(xué)科分類Communications in Computer and Information Science
圖書封面Titlebook: Artificial Intelligence; 17th Russian Confere Sergei O. Kuznetsov,Aleksandr I. Panov Conference proceedings 2019 Springer Nature Switzerlan
影響因子This book constitutes the proceedings of the 17th Russian Conference on Artificial Intelligence, RCAI 2019, held in Ulyanovsk, Russia, in October 2019.?.The 23 full papers presented along with 7 short papers in this volume were carefully reviewed and selected from 130 submissions. The conference deals with a wide range of topics, including multi-agent systems, intelligent robots and behaviour planning; automated reasoning and data mining; natural language processing and understanding of texts; fuzzy models and soft computing; intelligent systems and applications..
Pindex Conference proceedings 2019
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書目名稱Artificial Intelligence影響因子(影響力)




書目名稱Artificial Intelligence影響因子(影響力)學(xué)科排名




書目名稱Artificial Intelligence網(wǎng)絡(luò)公開度




書目名稱Artificial Intelligence網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Artificial Intelligence被引頻次




書目名稱Artificial Intelligence被引頻次學(xué)科排名




書目名稱Artificial Intelligence年度引用




書目名稱Artificial Intelligence年度引用學(xué)科排名




書目名稱Artificial Intelligence讀者反饋




書目名稱Artificial Intelligence讀者反饋學(xué)科排名




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Redistributing Animats Between Groupss. The purpose of this study is to implement a complex regulatory behavior of animat groups using previously created models and methods. The applicability of this approach is demonstrated by the task of redistributing animats between groups. To accomplish this, the paper proposes to implement a mech
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Hierarchical Control Architecture for a Learning Robot Based on Heterogenic Behaviorsp-level control algorithm is proposed that switches control between base algorithms: Q-learning, random walk and a rule-based planning. The algorithm is implemented as a software module and is verified by the example of the task of finding a given door in a building of complex planning. The task is
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Using a Hamming Neural Network to Predict Bond Strength of Welded Connectionsn algorithm for encoding information on dynamic resistance into bipolar signals required for a Hamming neural network tuning and operation..A computer program that implements a neural network based on the proposed algorithm has been developed. The results of the neural network training and testing a
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Logical Classification of Partially Ordered Datan procedures is proposed. These procedures are focused on specifying partial order relations on sets of feature values; they are based on a generalization of the classical concepts of logical classification. It is shown that learning a correct logical classifier requires solution of an intractable d
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