Integrating ACT-R Cognitive Models with the Unity Game Engine

Cognitive architectures are computational frameworks that can be used to develop computational models of human cognitive processes (Langley et al., 2009; Taatgen & Anderson, 2010; Thagard, 2012). Cognitive architectures have been useful in terms of advancing our understanding of human cognition in specific task environments, and they have also been used to support the development of a variety of intelligent systems and agents (e.g., cognitive robots). Although a variety of cognitive architectures are available, such as SOAR (Laird, 2012; Laird et al., 1987), ACT-R (Anderson, 2007; Anderson et al., 2004) and CLARION (Sun, 2006a; Sun, 2007), the focus of the current chapter is on ACT-R. ACT-R is a rule-based system that has been widely used by cognitive scientists to model aspects of human cognitive performance. It is also one of the few cognitive architectures that has an explicit link to research in the neurocognitive domain: the structural elements of the core ACT-R architecture (i.e., its modules and buffers) map onto different regions of the human brain (Anderson, 2007), and this enables cognitive modelers to make predictions about the activity of different brain regions at specific junctures in a cognitive task (see Anderson et al., 2007) 1 .