Hiroki Sayama is a Japanese artificial life and complex systems scientist. He is a SUNY Distinguished Professor in the School of Systems Science and Industrial Engineering at Binghamton University, where he directs the Binghamton Center of Complex Systems (CoCo). Trained in information science at the University of Tokyo, he first made his mark in the field of artificial life with “evoloops,” the first self-reproducing cellular automaton loops shown to undergo genuine Darwinian evolution. He is the author of the freely available textbook “Introduction to the Modeling and Analysis of Complex Systems,” and over 260 peer-reviewed papers. He previously served as chief editor of the journal Complexity and as the vice president of the International Society for Artificial Life. A dedicated community builder, Sayama currently serves as the vice chair of the IEEE Computational Intelligence Society’s Task Force on Artificial Life and Complex Adaptive Systems and as an elected council, executive committee and CCS steering committee member of the Complex Systems Society. He also serves as vice president and board member of the Network Science Society, and founded the low-cost Northeast Regional Conference on Complex Systems and the open-access Northeast Journal of Complex Systems.
In this deep and far-reaching InterDialogue, recorded at the 2026 Conference on Complex Systems in Binghamton, which Sayama chaired, we trace the story of evoloops from John von Neumann’s self-reproducing automata to Christopher Langton’s loops to Sayama’s own pioneering work, before turning to his current research on open-ended artificial systems and the ongoing effort to define life itself. We explore the gap between the micro and the macro across disciplines, his view that life unfolds at every scale simultaneously, the Carl Sagan-inspired fascination with endless processes that has guided his career, and his work on adaptive networks, in which structure and dynamics co-evolve.
The conversation then turns to building open and accessible scientific communities, the value of interdisciplinarity, and the importance of listening when tackling real-world problems, as well as his surprising research showing that more isolated, locally connected “small world” networks can generate more diverse, higher-quality ideas than fully connected ones. We close with his concern that AI is homogenizing human thought, and his notion that ideas, and perhaps AI itself, are literally living, evolving organisms.
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