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Experience generalization for multi-agent reinforcement learning
(Institute of Electrical and Electronics Engineers (IEEE), Computer Soc, 2001-01-01)
On-line learning methods have been applied successfully in multi-agent systems to achieve coordination among agents. Learning in multi-agent systems implies in a non-stationary scenario perceived by the agents, since the ...
Agente etiológico, Tratamiento empírico , Aplicación del qSOFA y la relación con la mortalidad en pacientes adultos con Síndrome Febril Neutropénico en un hospital público del Perú
(Universidad Peruana de Ciencias Aplicadas (UPC)PE, 2020-07-14)
Objetivo: Determinar la relación del tipo de agente etiológico, el uso de un tratamiento empírico y la aplicación del score qSOFA en la mortalidad en pacientes que poseen el de síndrome neutropénico febril en el hospital ...
Factores relevantes de la inestabilidad del mercado petrolero
(Universidad Externado de Colombia, 2021-07-01)
El mercado petrolero es inestable e impredecible debido al impacto de los elementos politicos, militares, tecnologicos y climaticos. La nueva y estrecha relación con el mercado inanciero, en particular con los mercados a ...
DeepQ learning in Atari Games
(2018-11)
The aim of this paper is to develop an AI agent with self-learning capabilities that is able to play classical Atari console games without human intervention and achieve next to human level performance. In order to achieve ...
Coxiella burnetii, the agent of Q fever in Brazil: its hidden role in seronegative arthritis and the importance of molecular diagnosis based on the repetitive element IS1111 associated with the transposase gene
(Fundação Oswaldo Cruz. Instituto Oswaldo Cruz., 2017)
Molecular identification of the agent of Q fever - Coxiella burnetii - in domestic animals in State of Rio de Janeiro, Brazil
(Sociedade Brasileira de Medicina Tropical, 2015)
Double Q-PID algorithm for mobile robot control
(Pergamon-Elsevier Science Ltd, 2019-12-15)
Many expert systems have been developed for self-adaptive PID controllers of mobile robots. However, the high computational requirements of the expert systems layers, developed for the tuning of the PID controllers, still ...