This project is being funded through the Learning and Intelligent Systems (LIS) initiative. A key aim of this initiative is to understand how highly complex intelligent systems could arise from simple initial knowledge through interactions with the environment. The best real-world example of such a system is the human infant who progresses from relatively simple abilities at birth to quite sophisticated abilities by two-years-of-age. This research focuses on the development of reaching by infants because (a) only rudimentary reaching ability is present at birth; (b) older infants use their arms in a sophisticated way to exploit and explore the world; and (c) the problems facing the infant are similar to those an artificial system would face. The project brings together two computer scientists who are experts on learning control algorithms and neural networks, and two psychologists who are experts on the behavioral and neural aspects of infant reaching, to investigate and test various algorithms by which infants might gain control over their arms. The proposed research focuses on the control strategies that infants use in executing reaches, how infants develop appropriate and adaptive modes of reaching, the mechanisms by which infants improve their ability to reach with age, the role of sensory information in controlling the reach, and how such knowledge might be stored in psychologically appropriate and computationally powerful ways. Preliminary results suggest that computational models that are appropriate for modeling the development of human reaching are different in significant ways from traditional computational models. Understanding the mechanisms by which intelligence can develop through learning can have significant impact in many scientific and engineering domains because the ability to build such systems would be simpler and faster than engineering a system with the intelligence specified by the engineer and because systems based on interactive learning could rapidly adapt to changing environmental conditions.
