Most early work in artificial intelligence can be described as searching through the “states” of a problem, using well-defined rules to change states, with the intention of discovering possible solutions for the problem. AI state space search began in the late 1940s and continues to the present day. Its most important years were between 1955 and the release of the Parallel Distributed Processing volumes of McClelland and Rumelhart in 1986. State space work in AI still remains very successful, however, with programs including IBM’s Deep Blue, the world champion chess playing program, and other applications seen later in Parts II–IV. This state space search approach to problem-solving is sometimes referred to as GOFAI, or good old-fashioned AI.