Results 141 to 150 of about 34,803,504 (287)
Acquiring musculoskeletal skills with curriculum-based reinforcement learning - model weights
Here we provide the weights of the neural network policies used for the analysis presented in our article. The archives whose names start with a number (01 - 32) correspond to the 32 curriculum steps to train the Baoding Balls policy which ranked first ...
Chiappa, Alberto +5 more
core +1 more source
This review establishes structure‐property‐mechanism relationships across six modification strategies for V‐based oxide water‐splitting electrocatalysts: lattice engineering, heteroatom doping, interface engineering, carbon‐based hybridization, morphology engineering, and surface reconstruction and pre‐catalyst design, where dissolution is reframed as ...
Youness El Issmaeli +4 more
wiley +1 more source
Learning Strict Nash Equilibria through Reinforcement [PDF]
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
Today, reinforcement learning is one of the most effective machine learning approaches in the tasks of automatically adapting computer systems to user needs. However, implementing this technology into a digital product requires addressing a key challenge:
Dmitry Vidmanov, Alexander Alfimtsev
doaj +1 more source
Architecture‐Driven Functional Coupling in Vertically Aligned Nanocomposites
Vertically aligned nanocomposites define a growth‐engineered architecture in which vertical interfaces, strain fields, defect pathways, and phase connectivity are created simultaneously. This review shows how these architectural features couple ferroic, optical, ionic, electrochemical, and device responses, establishing design rules and open challenges
Md Shatil Islam‐Shanto +4 more
wiley +1 more source
ED2: environment dynamics decomposition world models for continuous control
Model-based reinforcement learning (MBRL) achieves significant sample efficiency in practice in comparison to model-free RL, but its performance is often limited by the existence of model prediction error.
Yifu Yuan +4 more
doaj +1 more source
Nitride MXenes remain constrained by a persistent gap between computational prediction and experimental realization. This Review identifies the thermodynamic, kinetic, and chemical barriers limiting their synthesis, critically evaluates emerging fabrication routes, and proposes a multidimensional computational‐experimental framework to accelerate the ...
Naresh Varnakavi, Masoud Soroush
wiley +1 more source
Probability Matching and Reinforcement Learning* [PDF]
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
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
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei +9 more
wiley +1 more source

