can be represented through a variety of ways. Comparison with other cognitive architectures To compare with a few other cognitive architectures (Sun, 2016): ACT-R employs a division between procedural and declarative memory that is somewhat similar to CLARION’s distinction between the Action-Centered Subsystem and the Non-Action-Centered Subsystem. However, ACT-R does not have a clear-cut (process-based or representation-based) distinction between implicit and explicit processes, which is a fundamental assumption in the CLARION theory. Soar does not include a clear representation-based or process-based difference between implicit and explicit cognition, or between procedural and declarative memory; it is based on the ideas of problem spaces, states, and operators. When there is an outstanding goal on the goal stack, different productions propose different operators and operator preferences for accomplishing the goal. EPIC adopts a production system similar to ACT-R’s. However, it does not include the dichotomy of implicit and explicit processes, which is essential in CLARION. Theoretical applications CLARION has been used to account for a variety of psychological data (Sun, 2002, 2016), such as the serial reaction time task, the artificial grammar learning task, the process control task, a categorical inference task, an alphabetical arithmetic task, and the Tower of Hanoi task. The serial reaction time and process control tasks are typical implicit learning tasks (mainly involving implicit reactive routines), while the Tower of Hanoi and alphabetic arithmetic are high-level cognitive skill acquisition tasks (with a significant presence of explicit processes). In addition, extensive work has been done on a complex minefield navigation task, which involves complex sequential decision-making. Work on organizational decision tasks and other social simulation tasks (e.g., Naveh and Sun, 2006), as well as meta-cognitive tasks, has also been initiated. Other applications of the cognitive architecture include simulation of creativity (Helie and Sun, 2010) and addressing the computational basis of consciousness (or artificial consciousness) (Coward and Sun, 2004). References Coward, L.A. & Sun, R. (2004). Criteria for an effective theory of consciousness and some preliminary attempts. Consciousness and Cognition, 13, 268-301. Helie, H. and Sun, R. (2010). Incubation, insight, and creative problem solving: A unified theory and a connectionist model. Psychological Review, 117, 994-1024. Naveh, I. & Sun, R. (2006). A cognitively based simulation of academic science. Computational and Mathematical Organization Theory, 12, 313-337. Sun, R. (2002). Duality of the Mind: A Bottom-up Approach Toward Cognition. Mahwah, NJ: Lawrence Erlbaum Associates. Sun, R. (2016). Anatomy of the Mind: Exploring Psychological