Results 61 to 70 of about 580,002 (195)
A survey of benchmarking frameworks for reinforcement learning [PDF]
, 2020 Reinforcement learning has recently experienced increased prominence in the machine learning community. There are many approaches to solving reinforcement learning problems with new techniques developed constantly. When solving problems using reinforcement learning, there are various difficult challenges to overcome.
arxiv +1 more source
Experimental Investigation of Steel Plate Shear Walls under Shear-Compression Interaction
Shock and Vibration, 2019 Four scaled one-storey single-bay steel plate shear wall (SPSW) specimens with unstiffened panels were tested to determine their behaviour under cyclic loadings. The shear walls had moment-resisting beam-to-column connections.
Yang Lv +5 more
doaj +1 more source
External Prestressing Bridge Reinforcement Technology Review
MATEC Web of Conferences, 2015 Externally prestressed bridge can not only limit and reduce the cracks and deformation of the structure, improve the rigidity and bearing capacity of structure, improve the stress state of structure, but also have less interference for bridge operation ...
Zhu Hanbing, Yang Yaxun, Fan Weiya
doaj +1 more source
Reactive Reinforcement Learning in Asynchronous Environments
Frontiers in Robotics and AI, 2018 The relationship between a reinforcement learning (RL) agent and an asynchronous environment is often ignored. Frequently used models of the interaction between an agent and its environment, such as Markov Decision Processes (MDP) or Semi-Markov Decision
Jaden B. Travnik +6 more
doaj +1 more source
Recurrence for vertex-reinforced random walks on Z with weak reinforcements [PDF]
arXiv, 2014 We prove that any vertex-reinforced random walk on the integer lattice with non-decreasing reinforcement sequence $w$ satisfying $w(k) = o(k^{\alpha})$ for some $\alpha < 1/2$ is recurrent. This improves on previous results of Volkov (2006) and Schapira (2012).
arxiv
THE SUBSTITUTABILITY OF REINFORCERS [PDF]
Journal of the Experimental Analysis of Behavior, 1993 Substitutability is a construct borrowed from microeconomics that describes a continuum of possible interactions among the reinforcers in a given situation. Highly substitutable reinforcers, which occupy one end of the continuum, are readily traded for each other due to their functional similarity.
Leonard Green, Debra E. Freed
openaire +3 more sources
Large deviations in the reinforced random walk model on trees [PDF]
arXiv, 2012 In this paper, we consider the linearly reinforced and the once-reinforced random walk models in the transient phase on trees. We show the large deviations for the upper tails for both models. We also show the exponential decay for the lower tail in the once-reinforced random walk model.
arxiv
Distilling Neuron Spike with High Temperature in Reinforcement Learning Agents [PDF]
arXiv, 2021 Spiking neural network (SNN), compared with depth neural network (DNN), has faster processing speed, lower energy consumption and more biological interpretability, which is expected to approach Strong AI. Reinforcement learning is similar to learning in biology. It is of great significance to study the combination of SNN and RL.
arxiv
Coupling, Reinforcement, and Speciation [PDF]
The American Naturalist, 2018 During the process of speciation, populations may diverge for traits and at their underlying loci that contribute barriers to gene flow. These barrier traits and barrier loci underlie individual barrier effects, by which we mean the contribution that a barrier locus or trait-or some combination of barrier loci or traits-makes to overall isolation.
Butlin, R.K., Smadja, C.M.
openaire +7 more sources
Transverse Reinforcement in Reinforced Concrete Columns
sspjce, 2013 Abstract In the article we are dealing with the influence of transverse reinforcement to the resistance of a cross-section of the reinforced concrete columns and also with the effective detailing of the column reinforcement. We are verifying the correctness of design guides for detailing of transverse reinforcement.
Peter Veróny, Štefan Gramblička
openaire +3 more sources