Results 111 to 120 of about 6,531,013 (293)
Adaptive Foam 3D Printing of Ultralight and Multifunctional Materials
Advanced Engineering Materials, EarlyView.Adaptive foam 3D printing, enabled by expandable microspheres, imparts cellular structures to thermoplastic and thermosetting polymers, manufactured through a variety of processes including fused filament fabrication, direct ink writing, digital light processing, and inkjet printing.
Nariman Rajabifar, Amir Ameli
wiley +1 more source
Reinforcement learning or active inference? [PDF]
, 2009 This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception.
Friston, K. +17 more
core +1 more source
Multi-agent reinforcement learning for planning and scheduling multiple goals
, 2000 Recently, reinforcement learning has been proposed as an effective method for knowledge acquisition of the multiagent systems. However, most researches on multiagent system applying a reinforcement learning algorithm focus on the method to reduce ...
Arai, Sachiyo +2 more
core +1 more source
Advanced Engineering Materials, EarlyView.HEA interlayers offer a versatile route for joining high‐performance structural materials. Their compositional and structural design regulates interfacial reactions, suppresses brittle IMCs, and improves metallurgical bonding. Sandwich interlayers further integrate defect healing with precipitation strengthening, enabling improved strength–ductility ...
Lin Yuan +4 more
wiley +1 more source
Supporting AI Readiness Through Digital Workflows in Materials Science
Advanced Engineering Materials, EarlyView.Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns +67 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.This study proposes a potential device design for joint cartilage replacement. Silica‐polytetrahydrofuran (SiO2‐PolyTHF) hybrids with customizable mechanical properties were developed to mimic the characteristics of a natural meniscus. These were synthesized through a two‐pot sol–gel hybrid process.
Yu‐Chien Lin +12 more
wiley +1 more source
Dog Behaviour - Effect of Delay To Reinforcement [PDF]
, 2012 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
Reinforcement Learning for Blackjack [PDF]
, 2009 This paper explores the development of an Artificial Intelligence system for an already existing framework of card games, called SKCards, and the experimental results obtained from this. The current Artificial intelligence in the SKCards Blackjack is highly flawed. Reinforcement Learning was chosen as the method to be employed.
openaire +2 more sources
Advanced Functional Materials, EarlyView.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
Knowledge and Ignorance in Reinforcement Learning [PDF]
, 2011 The field of Reinforcement Learning is concerned with teaching agents to take optimal decisions to maximize their total utility in complicated environments. A Reinforcement Learning problem, generally described by the Markov Decision Process formalism,
Ramachandran, Deepak
core