Soar[1] is a cognitive architecture,[2] originally created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University.
The goal of the Soar project is to develop the fixed computational building blocks necessary for general intelligent agents – agents that can perform a wide range of tasks and encode, use, and learn all types of knowledge to realize the full range of cognitive capabilities found in humans, such as decision making, problem solving, planning, and natural-language understanding. It is both a theory of what cognition is and a computational implementation of that theory. Since its beginnings in 1983 as John Laird’s thesis, it has been widely used by AI researchers to create intelligent agents and cognitive models of different aspects of human behavior. The most current and comprehensive description of Soar is the 2012 book, The Soar Cognitive Architecture.[1]
Rosenbloom continued to serve as co-principal investigator after moving to Stanford University, then to the University of Southern California's Information Sciences Institute. It is now maintained and developed by John Laird's research group at the University of Michigan.