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META-Learning State-based Eligibility Traces for More Sampl..:

, In: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems,

Zhao, Mingde ; Luan, Sitao ; Porada, Ian.. - p. 1647-1655 , 2020

Link: https://dl.acm.org/doi/10.5555/3398761.3398950

RT 
T1 <cTitle>Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems</cTitle>: T1 <Title>META-Learning State-based Eligibility Traces for More Sample-Efficient Policy Evaluation</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3398950&Exemplar=1&LAN=DE
				
A1 Zhao, Mingde
A1 Luan, Sitao
A1 Porada, Ian
A1 Chang, Xiao-Wen
A1 Precup, Doina
PB International Foundation for Autonomous Agents and Multiagent Systems
YR 2020
K1 auxiliary task
K1 function approximation
K1 hyperparameter adaptation
K1 meta-learning
K1 reinforcement learning
K1 temporal difference learning
K1 Theory of computation
K1 Design and analysis of algorithms
K1 Online algorithms
K1 Online learning algorithms
K1 Computing methodologies
K1 Machine learning
K1 Machine learning algorithms
K1 Dynamic programming for Markov decision processes
K1 Temporal difference learning
K1 Machine learning approaches
K1 Markov decision processes
K1 Learning paradigms
K1 Reinforcement learning
SP 1647
OP 1655
LK http://dx.doi.org/https://dl.acm.org/doi/10.5555/3398761.3398950
DO https://dl.acm.org/doi/10.5555/3398761.3398950
SF ELIB - SuUB Bremen

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