Learning Path

This path provides a rigorous, interdisciplinary introduction to artificial life (ALife) within the broader context of complexity science. It moves from foundational concepts in complex systems and biological self-organization to core ALife methodologies such as agent-based modeling, evolutionary computation, and artificial chemistries, culminating in applications and contemporary research frontiers. Designed for advanced graduate students with an interest in the conceptual and computational underpinnings of life-as-it-could-be.