We have previously described an incremental learning algorithm, Learn++ .NC, for learning from new datasets that may include new concept classes without accessing previously seen d...
Gregory Ditzler, Michael D. Muhlbaier, Robi Polika...
In reinforcement learning problems, an agent has the task of learning a good or optimal strategy from interaction with his environment. At the start of the learning task, the agent...
Tom Croonenborghs, Kurt Driessens, Maurice Bruynoo...
We present an anytime multiagent learning approach to satisfy any given optimality criterion in repeated game self-play. Our approach is opposed to classical learning approaches fo...
This poster presents an ongoing European project: Language Technologies for Lifelong Learning (LTfLL). The aim of the project is to create a next-generation of support and advice ...
Adriana J. Berlanga, Peter van Rosmalen, Stefan Tr...
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples and thereby increase speed a...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...