Results 141 to 150 of about 171,350 (313)

Recursive Backwards Q-Learning in Deterministic Environments [PDF]

arXiv
Reinforcement learning is a popular method of finding optimal solutions to complex problems. Algorithms like Q-learning excel at learning to solve stochastic problems without a model of their environment. However, they take longer to solve deterministic problems than is necessary.
arxiv  

Functional Biomaterials Derived from Protein Liquid–Liquid Phase Separation and Liquid‐to‐Solid Transition

Advanced Materials, EarlyView.
Protein can undergo liquid–liquid phase separation and liquid‐to‐solid transition to form liquid condensates and solid aggregates. These phase transitions can be influenced by post‐translational modifications, mutations, and various environmental factors.
Tianchen Li, Dea Ilhamsyah, Benedict Tai, Yi Shen   +3 more
wiley   +1 more source

Scaling Up Q-Learning via Exploiting State-Action Equivalence. [PDF]

Entropy (Basel), 2023
Lyu Y, Côme A, Zhang Y, Talebi MS.
europepmc   +1 more source

Self-Play Ensemble Q-learning enabled Resource Allocation for Network Slicing [PDF]

arXiv
In 5G networks, network slicing has emerged as a pivotal paradigm to address diverse user demands and service requirements. To meet the requirements, reinforcement learning (RL) algorithms have been utilized widely, but this method has the problem of overestimation and exploration-exploitation trade-offs.
arxiv  

The Structure‐Mechanics Relationship of Bamboo‐Epidermis and Inspired Composite Design by Artificial Intelligence

Advanced Materials, EarlyView.
This article investigates the micromechanics of bamboo epidermis, focusing on how anisotropic silica particle distributions enhance toughness. By integrating experimental imaging, 3D printing, and generative AI, the study develops bio‐inspired particle‐reinforced composites with mechanical properties akin to bamboo.
Zhao Qin, Aymeric Pierre Destree
wiley   +1 more source

AHT-QCN: Adaptive Hunt Tuner Algorithm Optimized Q-learning Based Deep Convolutional Neural Network for the Penetration Testing

Cybernetics and Information Technologies
Penetration Testing (PT), which mimics actual cyber attacks, has become an essential procedure for assessing the security posture of network infrastructures in recent years.
Railkar Dipali, Joshi Shubhalaxmi
doaj   +1 more source

Una estrategia híbrida de aprendizaje por refuerzo informada por RRT* para la planificación de caminos de robots móviles en minería a cielo abierto

Revista Iberoamericana de Automática e Informática Industrial RIAI
Este trabajo introduce una estrategia híbrida de planificación de caminos para vehículos robóticos tipo diferencial, combinando métodos de aprendizaje por refuerzo con técnicas de muestreo aleatorio.
Sebastian Zapata, Ricardo Urvina, Katherine Aro, Eduardo Aguilar, Fernando Auat Cheein, Alvaro Prado   +5 more
doaj   +1 more source

A New Type of Learning Automata with Q-Learning Features

, 1999
Fei Qian, Seiichi Koakutsu, Hironori Hirata   +2 more
openalex   +2 more sources

Chiroferromagnetic Quantum Dots for Chiroptical Synapse (ChiropS)

Advanced Materials, EarlyView.
Chiroptical activity is enhanced by up to 0.003 in the g‐factor through the induction of ferromagnetism in quantum dots. A chiroptical neuromorphic synapse, composed of chiroferromagnetic quantum dots, generates different synaptic weights from multiple wavelengths and circularly polarized light.
Junyoung Kwon, Jae Bum Jeon, Walber Gonçalves Guimarães Júnior, Min Gu Lee, Changhyeon Lee, Geunyoung Kim, Hanchan Song, Woon Hyung Cheong, Sung Gap Im, André F. de Moura, Kyung Min Kim, Jihyeon Yeom   +11 more
wiley   +1 more source

Q-learning Based Meta-Heuristics for Scheduling Bi-Objective Surgery Problems with Setup Time

Complex System Modeling and Simulation
Since the increasing demand for surgeries in hospitals, the surgery scheduling problems have attracted extensive attention. This study focuses on solving a surgery scheduling problem with setup time. First, a mathematical model is created to minimize the
Ruixue Zhang, Hui Yu, Adam Slowik, Kaizhou Gao   +3 more
doaj   +1 more source