Results 61 to 70 of about 1,056,132 (188)
Applied Artificial Intelligence, 2023 Nowadays, mobile robots are being widely employed in various settings, including factories, homes, and everyday tasks. Achieving successful implementation of autonomous robot movement largely depends on effective route planning.
Jieren Tan
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Deep reinforcement learning for imbalanced classification [PDF]
Applied Intelligence, 2020 Data in real-world application often exhibit skewed class distribution which poses an intense challenge for machine learning. Conventional classification algorithms are not effective in the case of imbalanced data distribution, and may fail when the data distribution is highly imbalanced.
Enlu Lin, Qiong Chen, Xiaoming Qi
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Routing algorithms as tools for integrating social distancing with emergency evacuation
Scientific Reports, 2021 One of the lessons from the COVID-19 pandemic is the importance of social distancing, even in challenging circumstances such as pre-hurricane evacuation. To explore the implications of integrating social distancing with evacuation operations, we describe
Yi-Lin Tsai +3 more
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Collaborative Deep Reinforcement Learning
CoRR, 2017 Besides independent learning, human learning process is highly improved by summarizing what has been learned, communicating it with peers, and subsequently fusing knowledge from different sources to assist the current learning goal. This collaborative learning procedure ensures that the knowledge is shared, continuously refined, and concluded from ...
Kaixiang Lin, Shu Wang, Jiayu Zhou
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Deep Ordinal Reinforcement Learning [PDF]
, 2020 replaced figures for better visibility, added github repository, more details about source of experimental results, updated target value calculation for standard and ordinal Deep Q ...
Alexander Zap +2 more
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A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI LettersCyber‐attacks are gradually becoming more sophisticated and highly frequent nowadays, and the significance of network intrusion detection systems has become more pronounced.
Wanrong Yang +3 more
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Improvement of Deep Reinforcement Learning Using Curriculum in Game Environment
مجله پژوهش در علوم توانبخشی, 2020 Introduction: Training deep curriculum learning is a kind of smart agent training in which, first the simple acts, and then, the difficult acts are trained to smart agent.
Mohammadreza Mohammadnejad +2 more
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A Deep Reinforcement Learning Chatbot
CoRR, 2017 40 pages, 9 figures, 11 ...
Iulian Vlad Serban +17 more
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Discover Artificial IntelligenceThis study discusses the application of deep reinforcement learning in the design and optimization of English continuing education teaching content. Aiming at the one-size-fits-all problem in the traditional education model, it puts forward personalized ...
Jinfeng Ma
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EnergiesRecent breakthroughs in artificial intelligence are accelerating the intelligent transformation of vehicles. Vehicle electronic and electrical architectures are converging toward centralized domain controllers.
Dagang Lu +11 more
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