A particularly stinging criticism of the entire artificial intelligence enterprise has been its’ ability to produce systems that are far more capable than a typical human on domain-specific tasks but its’ striking inability to produce systems that perform some of the simplest tasks that toddlers excel at. While various proposals have been made regarding the construction of a “mechanical child,” going as far back as Turing (Turing 1950) and more recently in the realm of robotics, it has been rare for developers of architectures for general intelligence to inform their work with results from child development in the abstract. We describe a cognitive architecture in terms of a set of domain-general functional primitives capable of succeeding on a variety of well-known tasks from the child development literature spanning the so-called “core” cognitive domains of infant physics and folk psychology. Finally, we discuss the advantages of this approach in moving forward toward modeling other sorts of higher-order cognition, including the understanding and use of natural language.
Submitted: Sep 10, 2008