This thesisinvestigates self-assembled behavior as a foundation for conceptualizing architecture as an autonomous, agentic behavioral system. The research addresses three core questions: how intelligent behaviors emerge within contemporary artificial intelligence developments; how self-assembled machine agents can be implemented to demonstrate inter-agent cooperation; and how a collective system can be constructed to enable architecture to assume an active and participatory role in the relationship between humans and space.

The methodology follows a progressive inference path, beginning with the design of individual machine behaviors integrated with artificial intelligence modules that embed self-awareness. This development then scales toward collective intelligence, forming a self-organizing dynamic system driven by inter-agent cooperation. Through this individual-to-collective trajectory, architecture is reconceptualized as an autonomous and continuously evolving agent capable of dynamically responding to its context.

Ultimately, this research aims to reposition architecture from a static problem-solving solution to a dynamic, life-like participant in the urban dialogue, capable of engaging in continuous conversation with itsinhabitants and the broadersocietal contex