Results 41 to 50 of about 301,921 (265)
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
doaj +1 more source
Multi-Agent Deep Reinforcement Learning with Human Strategies
, 2019 Deep learning has enabled traditional reinforcement learning methods to deal with high-dimensional problems. However, one of the disadvantages of deep reinforcement learning methods is the limited exploration capacity of learning agents.
Nahavandi, Saeid +2 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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Quantum Deep Recurrent Reinforcement Learning
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023 Recent advances in quantum computing (QC) and machine learning (ML) have drawn significant attention to the development of quantum machine learning (QML). Reinforcement learning (RL) is one of the ML paradigms which can be used to solve complex sequential decision making problems.
openaire +2 more sources
Crop Yield Prediction Using Deep Reinforcement Learning Model for Sustainable Agrarian Applications
IEEE Access, 2020 Predicting crop yield based on the environmental, soil, water and crop parameters has been a potential research topic. Deep-learning-based models are broadly used to extract significant crop features for prediction. Though these methods could resolve the
Dhivya Elavarasan +1 more
doaj +1 more source
, 2018 Under review for Morgan & Claypool: Synthesis Lectures in Artificial Intelligence and Machine ...
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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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An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning
, 2021 DQN (Deep Q-Network) is a method to perform Q-learning for reinforcement learning using deep neural networks. DQNs require a large buffer and batch processing for an experience replay and rely on a backpropagation based iterative optimization, making ...
Matsutani, Hiroki +2 more
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Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system
FEBS Letters, EarlyView.Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley +1 more source
Deep Ordinal Reinforcement Learning
, 2019 Reinforcement learning usually makes use of numerical rewards, which have nice properties but also come with drawbacks and difficulties. Using rewards on an ordinal scale (ordinal rewards) is an alternative to numerical rewards that has received more ...
C Wirth, CJ Watkins, RS Sutton, V Mnih
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