Results 111 to 120 of about 198,528 (317)
PILCO: A Model-Based and Data-Efficient Approach to Policy Search [PDF]
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
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A Dislocation Perspective on Strength and Toughness in Ceramics
Dislocations in ceramics enjoy a long but yet under‐appreciated history. The three research waves for dislocations in ceramics highlight the topic evolution over the last 90 years. This review focuses on the impact of dislocation on strength and toughness in ceramics.
Xufei Fang
wiley +1 more source
Scaling Reinforcement Learning Paradigms for Motor Control
Reinforcement learning offers a general framework to explain rewardrelated learning in artificial and biological motor control. However, current reinforcement learning methods rarely scale to high dimensional movement systems and mainly operate in ...
Vijayakumar, S.; id_orcid +2 more
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This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner +14 more
wiley +1 more source
Reinforcement learning is widely used for control applications and has also been successfully implemented for efficient energy management within hybrid electric vehicles.
Mohamed Nadir Boukoberine +3 more
doaj +1 more source
Review of Generative Reinforcement Learning Based on Sequence Modeling [PDF]
Reinforcement learning is a branch of machine learning on how to learn decisions,which is a sequential decision-making problem that involves repeatedly interacting with the environment to find the optimal strategy through trial and error.Reinforcement ...
YAO Tianlei, CHEN Xiliang, YU Peiyi
doaj +1 more source
Corrected version of paper appearing in ICML ...
Christos Dimitrakakis +1 more
openaire +3 more sources
Dog Behaviour - Effect of Delay To Reinforcement
Dogs were fed dry food as reinforcement and were required to touch a wand with their nose to get that reinforcement. In the first study, half the dogs were given immediate reinforcement, while for the remaining dogs reinforcement was delayed by two ...
Lord, Sarah
core
Wafer‐scale two‐dimensioanl In2Se3 oxidized into InOx on sodium‐embedded beta‐alumina enables multifunctional reconfigurable electronics. Sodium ions accumulate within distinct spatial distribution under drain‐controlle and gate‐controlled operation. Drain‐control operation gives controllability of ultraviolet‐driven optoelectronic synaptic conductance
Jinhong Min +13 more
wiley +1 more source

