Results 41 to 50 of about 298,347 (266)

A Method to Plan the Path of a Robot Utilizing Deep Reinforcement Learning and Multi-Sensory Information Fusion

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
doaj   +1 more source

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

Deep learning, reinforcement learning, and world models

Neural Networks, 2022
Deep learning (DL) and reinforcement learning (RL) methods seem to be a part of indispensable factors to achieve human-level or super-human AI systems. On the other hand, both DL and RL have strong connections with our brain functions and with neuroscientific findings.
Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto   +7 more
openaire   +3 more sources

Deep Reinforcement Learning for Dialogue Generation

, 2016
Recent neural models of dialogue generation offer great promise for generating responses for conversational agents, but tend to be shortsighted, predicting utterances one at a time while ignoring their influence on future outcomes.
Galley, Michel, Gao, Jianfeng, Jurafsky, Dan, Li, Jiwei, Monroe, Will, Ritter, Alan   +5 more
core   +1 more source

Deep Reinforcement Learning

, 2018
Under review for Morgan & Claypool: Synthesis Lectures in Artificial Intelligence and Machine ...
openaire   +3 more sources

Research Progress in Multi-Domain and Cross-Domain AI Management and Control for Intelligent Electric Vehicles

Energies
Recent breakthroughs in artificial intelligence are accelerating the intelligent transformation of vehicles. Vehicle electronic and electrical architectures are converging toward centralized domain controllers.
Dagang Lu, Yu Chen, Yan Sun, Wenxuan Wei, Shilin Ji, Hongshuo Ruan, Fengyan Yi, Chunchun Jia, Donghai Hu, Kunpeng Tang, Song Huang, Jing Wang   +11 more
doaj   +1 more source

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, P. M. Durairaj Vincent   +1 more
doaj   +1 more source

Deep Reinforcement Factorization Machines: A Deep Reinforcement Learning Model with Random Exploration Strategy and High Deployment Efficiency

Applied Sciences, 2022
In recent years, the recommendation system and robot learning are undoubtedly the two most popular application fields, and the core algorithms supporting these two fields are deep learning based on perception and reinforcement learning based on ...
Huaidong Yu, Jian Yin
doaj   +1 more source

A Survey and Critique of Multiagent Deep Reinforcement Learning

, 2019
Deep reinforcement learning (RL) has achieved outstanding results in recent years. This has led to a dramatic increase in the number of applications and methods.
Hernandez-Leal, Pablo, Kartal, Bilal, Taylor, Matthew E.   +2 more
core   +1 more source

Overview of molecular signatures of senescence and associated resources: pros and cons

FEBS Open Bio, EarlyView.
Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas, Sylvia Vagena, Pavlos Pantelis, Giorgos Theocharous, Russel Petty, Konstantinos Evangelou, Vassilis G. Gorgoulis   +6 more
wiley   +1 more source