Results 101 to 110 of about 6,930,474 (290)

Learning Strict Nash Equilibria through Reinforcement [PDF]

open access: yes
This paper studies the analytical properties of the reinforcement learning model proposed in Erev and Roth (1998), also termed cumulative reinforcement learning in Laslier et al (2001).
Ianni, Antonella
core  

Study on the standardization method of radiotelephony communication in low-altitude airspace based on BART

open access: yesFrontiers in Neurorobotics
The development of air traffic control (ATC) automation has been constrained by the scarcity and low quality of communication data, particularly in low-altitude complex airspace, where non-standardized instructions frequently hinder training efficiency ...
Weijun Pan, Boyuan Han, Peiyuan Jiang
doaj   +1 more source

Mechanics of Telson Ridges in Mantis Shrimp for Impact Analysis and Implications for Bioinspired Elastic Shell Designs

open access: yesAdvanced Functional Materials, EarlyView.
The mantis shrimp telson reveals how ridged biological shields control deformation under impact. Inspired by this architecture, telson‐inspired ridged curved shells transform ridge geometry and macroscopic curvature into bidirectional snap‐through, tunable stiffness, and enhanced hysteretic energy dissipation for multifunctional architected materials ...
Phani Saketh Dasika   +5 more
wiley   +1 more source

Probability Matching and Reinforcement Learning* [PDF]

open access: yes
Probability matching occurs when an action is chosen with a frequency equivalent to the probability of that action being the best choice. This sub-optimal behavior has been reported repeatedly by psychologist and experimental economist.
Javier Rivas
core  

Advances in 3D Bioprinting for Breast Cancer Modeling: Tumor Microenvironment, Metastasis, and Drug Screening

open access: yesAdvanced Healthcare Materials, EarlyView.
Three‐dimensional bioprinting transforms breast cancer modeling from simple constructs into spatially organized, multicellular, perfused, and patient‐derived platforms. This review shows how bioinks, cellular composition, architecture, and flow govern tumor behavior and drug response, while revealing why complexity alone is insufficient without ...
Mustafa Nakipoglu   +7 more
wiley   +1 more source

Microfluidic Engineering of Microgels: A Review of Emerging Technologies, Materials, Fabrication Strategies, and Applications

open access: yesAdvanced Healthcare Materials, EarlyView.
Recent advances in microfluidic technologies for microgel fabrication are critically reviewed, highlighting the capabilities and limitations of major microfluidic platforms and discussing how platform design, material selection, and crosslinking strategies influence microgel architecture and functionality. Current challenges and future opportunities in
Afshin Abrishamkar   +6 more
wiley   +1 more source

Automatic generation of ESL learning materials based on CEFR levels using reinforcement-tuned LLMs

open access: yesDiscover Artificial Intelligence
The automatic generation of CEFR-aligned learning materials remains a challenging task due to the difficulty of balancing linguistic accuracy, scalability, and adaptability.
Yi Zuo
doaj   +1 more source

Thermodynamic Limits to Molecular Doping in Conjugated Polymers: A Perspective on Phase Behavior and Miscibility

open access: yesAdvanced Materials, EarlyView.
Molecular doping of conjugated polymers is fundamentally constrained by thermodynamic phase behavior. This Perspective reframes doping efficiency and stability in terms of miscibility limits, binodals, and solvus boundaries, highlighting the role of effective interaction parameters and charge transfer.
Somayeh Kashani   +10 more
wiley   +1 more source

Optimal Control Drives Ultrafast and Energy‐Efficient Magnetization Switching in Van der Waals Magnets

open access: yesAdvanced Materials, EarlyView.
ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh   +2 more
wiley   +1 more source

Constrained Reinforcement Learning Under Model Mismatch

open access: yesCoRR
Existing studies on constrained reinforcement learning (RL) may obtain a well-performing policy in the training environment. However, when deployed in a real environment, it may easily violate constraints that were originally satisfied during training because there might be model mismatch between the training and real environments. To address the above
Zhongchang Sun   +3 more
openaire   +4 more sources

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