Previous bias shift approaches to predicate invention are not applicable to learning from positive examples only, if a complete hypothesis can be found in the given language, as ne...
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
In concurrent cooperative multiagent learning, each agent simultaneously learns to improve the overall performance of the team, with no direct control over the actions chosen by i...
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
Within the last few years, knowledge management has become one of the hottest subjects among organisational and information systems theorists and practitioners. Many find in it an...