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Task Rescheduling using Relational Reinforcement Learning
(IBERAMIA, 2012-12)
Generating and representing knowledge about heuristics for repair-based scheduling is a key issue in any rescheduling strategy to deal with unforeseen events and disturbances. Resorting to a feature-based propositional ...
Real-time rescheduling of production systems using relational reinforcement learning
(QUALIS CAPES (UFSC), 2011-12)
Most scheduling methodologies developed until now have laid down good theoretical foundations, but there is still the need for real-time rescheduling methods that can work effectively in disruption management. In this ...
Modelling shared attention through relational reinforcement learning
(SPRINGERDORDRECHT, 2012)
Shared attention is a type of communication very important among human beings. It is sometimes reserved for the more complex form of communication being constituted by a sequence of four steps: mutual gaze, gaze following, ...
Condition-Based maintenance with reinforcement learning for dry gas pipeline subject to internal corrosión
(MDPI, 2020)
Gas pipeline systems are one of the largest energy infrastructures in the world and are known to be very efficient and reliable. However, this does not mean they are prone to no risk. Corrosion is a significant problem in ...
SmartGantt - An intelligent system for real time rescheduling based on relational reinforcement learning
(Elsevier Science Ltd, 2012)
Multimodal mechanisms of human socially reinforced learning across neurodegenerative diseases
(Oxford University Press, 2021-03)
Social feedback can selectively enhance learning in diverse domains. Relevant neurocognitive mechanisms have been studied mainly in healthy persons, yielding correlational findings. Neurodegenerative lesion models, coupled ...