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Reinforcement learning using continuous states and interact..:

, In: Proceedings of the 2nd International Conference on Applications of Intelligent Systems,

Ayala, Angel ; Henríquez, Claudio ; Cruz, Francisco - p. 1-5 , 2019

Link: https://dl.acm.org/doi/10.1145/3309772.3309801

RT 
T1 <cTitle>Proceedings of the 2nd International Conference on Applications of Intelligent Systems</cTitle>: T1 <Title>Reinforcement learning using continuous states and interactive feedback</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3309801&Exemplar=1&LAN=DE
				
A1 Ayala, Angel
A1 Henríquez, Claudio
A1 Cruz, Francisco
PB ACM
YR 2019
K1 Q-learning
K1 continuous interactive reinforcement learning
K1 reinforcement learning
K1 Theory of computation
K1 Design and analysis of algorithms
K1 Mathematical optimization
K1 Continuous optimization
K1 Theory and algorithms for application domains
K1 Machine learning theory
K1 Reinforcement learning
K1 Models of computation
K1 Interactive computation
K1 Computer systems organization
K1 Architectures
K1 Other architectures
K1 Neural networks
K1 Computing methodologies
K1 Artificial intelligence
K1 Distributed artificial intelligence
K1 Intelligent agents
K1 Mathematics of computing
K1 Probability and statistics
K1 Stochastic processes
K1 Markov processes
SP 1
OP 5
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3309772.3309801
DO https://dl.acm.org/doi/10.1145/3309772.3309801
SF ELIB - SuUB Bremen

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