Model-based reinforcement learning

Results 161 to 170 of about 34,803,504 (287)

, 2018
, .
��
core

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source

Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics

Advanced Materials, EarlyView.
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair +3 more
wiley +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source

Soft Skins With Reversible Thickness Morphing: Materials, Mechanisms, and Applications

Advanced Materials, EarlyView.
Evolution of electronic skin (e‐skin) technologies toward adaptive, multifunctional soft skins. Phase I highlights early rigid and discrete sensory interfaces. Phase II shows the transition toward flexible, stretchable, and large‐area e‐skin. Phase III captures the emergence of computational e‐skin.
Oliver Ozioko, Chiamaka Akah, Ravinder Dahiya +2 more
wiley +1 more source

Predictive representations can link model-based reinforcement learning to model-free mechanisms. [PDF]

PLoS Comput Biol, 2017
Russek EM +4 more
europepmc +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source

SINDy-RL for interpretable and efficient model-based reinforcement learning. [PDF]

Nat Commun
Zolman N +4 more
europepmc +1 more source

Sustainable and Multifunctional Natural Macromolecular Polymers for Aqueous Zn Metal Batteries

Advanced Materials, EarlyView.
We comprehensively review the structure‐function relationships and regulatory mechanism of natural macromolecular polymers in stabilizing zinc anodes at the microscopic and mesoscopic scales. The interactions among polymer structures, optimization strategies, and regulatory mechanisms are discussed systematically summarizing recent related research ...
Yunuo Shi +13 more
wiley +1 more source

Spiking world model with multicompartment neurons for model-based reinforcement learning. [PDF]

Proc Natl Acad Sci U S A
Sun Y, Zhao F, Lyu M, Zeng Y.
europepmc +1 more source

fos: computer and information sciences
machine learning cs.lg
computer science - machine learning

reinforcement learning
artificial intelligence cs.ai
computer science - artificial intelligence

machine learning stat.ml
statistics - machine learning
deep reinforcement learning