s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Rapid increases in computing and communication performance are exacerbating the long-standing problem of performance-limited input/output. Indeed, for many otherwise scalable para...
Phyllis Crandall, Ruth A. Aydt, Andrew A. Chien, D...
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Evolutionary art has a long and distinguished history, and genetic programming is one of only a handful of AI techniques which is used in graphic design and the visual arts. A rece...
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic ...