Results 61 to 70 of about 9,252,589 (289)

A novel policy for pre-trained deep reinforcement learning for speech emotion recognition

, 2022
Deep Reinforcement Learning (deep RL) has gained tremendous success in gaming but it has rarely been explored for Speech Emotion Recognition (SER). In the RL literature, policy used by the RL agent plays a major role in action selection, however, there ...
Rana, Rajib, Sara Khalifa, Schuller, Björn W., Schuller, Bjorn W, Bjorn Schuller, Khalifa, Sara, Rajapakshe, Thejan, Thejan Rajapakshe, Rajib Rana, Jiajun Liu, Liu, Jiajun   +10 more
core   +1 more source

Polyphenol‐Inspired Materials for Agricultural Applications

Advanced Materials, EarlyView.
This review outlines the use of polyphenol‐inspired materials for sustainable agriculture, highlighting their molecular design, interfacial assembly, structure–property relationships, and prospects toward precision agriculture, climate resilience, ecosystem protection, and circular bioeconomy strategies.
Haofu Liu, Omid Mazaheri, Zhixing Lin, Tianzheng Wang, Jingqu Chen, Yuang Gu, Xia Liang, Deli Chen, Frank Caruso   +8 more
wiley   +1 more source

SafeAdapt: Provably Safe Policy Updates in Deep Reinforcement Learning

CoRR
Code available at: https://github.com/maxanisimov/provably-safe-policy ...
Maksim Anisimov, Francesco Belardinelli, Matthew Wicker   +2 more
openaire   +2 more sources

PILCO: A Model-Based and Data-Efficient Approach to Policy Search [PDF]

, 2011
04.07.13 KB. Ok to add accepted version to Spiral. Authors retain copyright.In this paper, we introduce PILCO, a practical, data-efficient model-based policy search method.
Rasmussen, Carl E, Deisenroth, Marc P
core  

Fully Dynamic Reorder Policies with Deep Reinforcement Learning for Multi-Echelon Inventory Management [PDF]

, 2022
The operation of inventory systems plays an important role in the success of manufacturing companies, making it a highly relevant domain for optimization.
Mu, Gang, Braun, Torsten, Hammler, Patric, Riesterer, Nicolas   +3 more
core  

Artificial Intelligence Meets Micro/Nanorobotics

Advanced Materials, EarlyView.
Artificial intelligence is transforming micro‐ and nanorobots from externally controlled, task‐specific machines into adaptive, autonomous systems. Machine learning, multimodal perception, digital twins, AI‐guided materials and geometry design enhance propulsion, localization, decision‐making, whichaccelerates clinical and environmental applications ...
Fatma M. Yurtsever, Minitha Cherukutty Ramakrishnan, Ian Kuula Ross, Ivan Zelinka, Hamed Shahsavan, Michal Otyepka, Martin Pumera   +6 more
wiley   +1 more source

Bioengineered Interfaces for Peripheral Nerve Sensory Restoration

Advanced Materials, EarlyView.
Half of amputees abandon their prosthetics for lack of feeling. This review charts the full path from peripheral nerve injury to restored sensation, through surgical, regenerative, noninvasive, and implanted approaches, and shows how injury type and interface material properties determine which strategy can deliver naturalistic feedback, and why ...
Sydney Swedick, Salim El Hadwe, Kesi Liang, George G. Malliaras, Damiano G. Barone   +4 more
wiley   +1 more source

Descriptors to Dynamics: A Materials and Device Perspective on in‐Materio Physical Reservoir Computing for Neuromorphic Edge Intelligence

Advanced Materials, EarlyView.
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh, Alif Syafiq Kamarol Zaman, Muzhen Xu, Yuki Usami, Saptarshi Das, Hirofumi Tanaka   +5 more
wiley   +1 more source

Cooperative Deep Reinforcement Learning Policies for Autonomous Navigation in Complex Environments

IEEE Access
A critical part of achieving robust and safe navigation for mobile robots is selecting the right navigation policies trained through simulation to operate effectively in real-world situations.
Van Manh Tran, Gon-Woo Kim
doaj   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source