Results 61 to 70 of about 33,184 (187)

Competitive Experience Replay

CoRR, 2019
Deep learning has achieved remarkable successes in solving challenging reinforcement learning (RL) problems when dense reward function is provided. However, in sparse reward environment it still often suffers from the need to carefully shape reward function to guide policy optimization.
Hao Liu, Alexander Trott, Richard Socher, Caiming Xiong   +3 more
openaire   +4 more sources

A Hash-Based RFID Authentication Mechanism for Context-Aware Management in IoT-Based Multimedia Systems

Sensors, 2019
With the technological advances in the areas of Machine-To-Machine (M2M) and Device-To-Device (D2D) communication, various smart computing devices now integrate a set of multimedia sensors such as accelerometers, barometers, cameras, fingerprint sensors,
Deebak B D, Fadi Al-Turjman, Leonardo Mostarda   +2 more
doaj   +1 more source

VTA neurons coordinate with the hippocampal reactivation of spatial experience

eLife, 2015
Spatial learning requires the hippocampus, and the replay of spatial sequences during hippocampal sharp wave-ripple (SPW-R) events of quiet wakefulness and sleep is believed to play a crucial role.
Stephen N Gomperts, Fabian Kloosterman, Matthew A Wilson   +2 more
doaj   +1 more source

Methodological Caveats in the Detection of Coordinated Replay between Place Cells and Grid Cells

Frontiers in Systems Neuroscience, 2017
At rest, hippocampal “place cells,” neurons with receptive fields corresponding to specific spatial locations, reactivate in a manner that reflects recently traveled trajectories.
John B. Trimper, John B. Trimper, Sean G. Trettel, Sean G. Trettel, Sean G. Trettel, Ernie Hwaun, Ernie Hwaun, Ernie Hwaun, Laura Lee Colgin, Laura Lee Colgin, Laura Lee Colgin   +10 more
doaj   +1 more source

CONSTITUTIONAL REPLAY LAW The Governing Rules of Replay-Authoritative Determination

The Constitutional Replay-Authority corpus has now defined the category of replay-authoritative systems, diagnosed the legitimacy gap those systems must address, supplied a taxonomy of constitutional concepts, identified the primitive architecture on ...
Otto, Larry
core   +2 more sources

On Experience Replay

, 2019
Reinforcement learning has proved to be of great utility in myriad set- tings; execution, however, may be costly due to sampling inefficiency. Experi- ence replay is used in reinforcement learning for efficient learning by recalling past experiences ...
Tan, Renzo Roel
core   +1 more source

Identifying approaches for attracting and training new entrants and the existing workforce in the Early Learning and Childcare sector

, 2018
First paragraph: This country report presents input to EU Strategy suggestions and guidelines for upskilling low- skilled people so they can cover future staff requirements.
Webb, Aleksandra, McQuaid, Ronald
core  

Automated Debugging Mechanisms for Orchestrated Cloud Infrastructures With Active Control and Global Evaluation

IEEE Access
Orchestration methods at Infrastructure-as-a-Service (IaaS) level automate the deployment, scaling, and management of virtualized resources, typically across multiple hosts and data centres.
Jozsef Kovacs, Bence Ligetfalvi, Robert Lovas   +2 more
doaj   +1 more source

La faute et son ralenti. Le cadrage temporel et visuel de l’action normée

Temporalités, 2017
In this paper, we examine the reflexive link between the temporal unfolding of a sports game and its broadcasting live on TV. Borrowing from a video-ethnography in the control-room of technicians producing video football matches in real-time, this ...
Laurent Camus
doaj   +1 more source

Attentive Experience Replay

, 2020
Experience replay (ER) has become an important component of deep reinforcement learning (RL) algorithms. ER enables RL algorithms to reuse past experiences for the update of current policy.
Li, Houqiang, Sun, Peiquan, Zhou, Wengang   +2 more
core   +1 more source