The objective of this paper is to study the existing methods for unsupervised object recognition and image categorization and propose a model that can learn directly from the outp...
Techniques that traditionally have been useful for retrieving same-domain analogies from small single-use knowledge bases, such as spreading activation and indexing on selected fe...
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...
Abstract—Memetics is a new science that has attracted increasing attentions in the recent decades. Beyond the formalism of simple hybrids, adaptive hybrids and memetic algorithms...
The effectiveness of simulation-based training for individual tasks – such as piloting skills – is well established, but its use for team training raises challenging technical...
David R. Traum, Jeff Rickel, Jonathan Gratch, Stac...