Most reinforcement learning models of animal conditioning operate under the convenient, though fictive, assumption that Pavlovian conditioning concerns prediction learning whereas...
Peter Dayan, Yael Niv, Ben Seymour, Nathaniel D. D...
Connectivity is central to pervasive computing environments. We seek to catalyze a world of rich and diverse connectivity through technologies that drastically simplify the task o...
George Lee, Peyman Faratin, Steven Bauer, John Wro...
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
There are many applications of multilayer neural networks to pattern classification problems in the engineering field. Recently, it has been shown that Bayes a posteriori probab...
The paper presents a framework called ECOS for Evolving COnnectionist Systems. ECOS evolve through incremental learning. They can accommodate any new input data, including new fea...