Title :
From ADP to the brain: Foundations, roadmap, challenges and research priorities
Author_Institution :
Eng. Directorate, Nat. Sci. Found., Arlington, VA, USA
Abstract :
This paper defines and discusses "Mouse Level Computational Intelligence" (MCLI) as a grand challenge for the coming century. It provides a specific roadmap to reach that target, citing relevant work and review papers and discussing the relation to funding priorities in two NSF funding activities. The ongoing Energy, Power and Adaptive Systems program (EPAS) and the recent initiative in Cognitive Optimization and Prediction (COPN). It elaborates on the first step, "vector intelligence," a challenge in the development of universal learning systems, which itself will require considerable new research to attain. This in turn is a crucial prerequisite to true functional understanding of how mammal brains achieve such general learning capabilities.
Keywords :
learning (artificial intelligence); COPN; EPAS program; MCLI; cognitive optimization and prediction; energy power and adaptive systems program; learning capabilities; mouse level computational intelligence; universal learning systems; vector intelligence; Approximation methods; Biological neural networks; Forecasting; Learning systems; Mice; Optimization; Vectors; ADP; Bayesian; control component; optimization; prediction; robust; stochastic processes; universal learning;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889359