Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2004.Page 205 blank.Includes bibliographical references (p. [197]-204).Cognitive development is one of nature's most important mechanisms for creating robustly adaptive intelligent creatures. From felids to oscines, developing animals are capable of learning in adverse environments with a reliability that often outpaces the current state-of-the-art in artificial intelligence (AI) The purpose of this thesis, therefore, is to examine how insights from cognitive development might be applied to the design of AI architectures. Starting with a targeted review of the ethological literature, I identify the key computational lessons of development, the fundamental conceptual insights that suggest intriguing new strategies for behavioral organization. These insights are then employed in the design of a developmental behavior architecture in which a hierarchical motivation-based behavior system is coupled to a distributed set of domain-specific learning tools. The architecture is deployed in a synthetic character (Hektor the mouse) whose challenge is to learn to play a competitive card matching game successfully against a human user. Evaluation of Hektor's performance on this task, at both qualitative and quantitative levels of description, reveal that the developmental architecture is capable of surmounting complex learning objectives in a novel and efficient manner. I conclude that the architecture presented here represents a valuable starting point for further consideration of developmental design principles.by Derek Eugen Lyons.S.M
