Here are entered works on a group of technologies and methods, including knowledge-based systems, neural networks, fuzzy set theory, genetic algorithms, and probabilistic and evidential approaches, that mimic the human ability to make decisions in an environment of uncertainty and imprecision. Works on computing that intelligently trades off implementation, storage, and/or result accuracy for performance or energy gains are entered under Approximate computing.
Here are entered works on the viewpoint in learning theory that individuals acquire knowledge by building it from innate capabilities interacting with the environment, as well as works on educational practices based upon this viewpoint.