This paper investigates basic research issues that need to be addressed for developing an architecture that enables repurposing of learning objects in a flexible way. Currently, t...
Katrien Verbert, Dragan Gasevic, Jelena Jovanovic,...
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
Reinforcement learning has been used for training game playing agents. The value function for a complex game must be approximated with a continuous function because the number of ...
Learning can be an effective way for robot systems to deal with dynamic environments and changing task conditions. However, popular singlerobot learning algorithms based on discou...
Hierarchical reinforcement learning has been proposed as a solution to the problem of scaling up reinforcement learning. The RLTOPs Hierarchical Reinforcement Learning System is an...