Category: Talks

David Krakauer on Emergent Political Economies and A Science of Possibility

The world is unfair — but how much of that unfairness is inevitable, and how much is just contingency? After centuries of efforts to arrive at formal theories of history, society, and economics, most of us still believe and act on what amounts to myth. Our predecessors can’t be faulted for their lack of data, but in 2022 we have superior resources we’re only starting to appreciate and use. In honor of the Santa Fe Institute’s new role as the hub of an international research network exploring Emergent Political Economies, we dedicate this new sub-series of Complexity Podcast to conversations on money, power, governance, and justice. Subscribe for a new stream of dialogues and trialogues between SFI’s own diverse scholastic community and other acclaimed political economists, historians, and authors of speculative fiction.

Read the full article at: complexity.simplecast.com

C. Brandon Ogbunu on Epistasis & The Primacy of Context in Complex Systems

Context is king: whether in language, ecology, culture, history, economics, or chemistry. One of the core teachings of complexity science is that nothing exists in isolation — especially when it comes to systems in which learning, memory, or emergent behaviors play a part. Even though this (paradoxically) limits the universality of scientific claims, it also lets us draw analogies between the context-dependency of one phenomenon and others: how protein folding shapes HIV evolution is meaningfully like the way that growing up in a specific neighborhood shapes educational and economic opportunity; the paths through a space of all possible four-letter words are constrained in ways very similar to how interactions between microbes impact gut health; how we make sense both depends on how we’ve learned and places bounds on what we’re capable of seeing.

Listen at: complexity.simplecast.com

How to Make Things Evolve by Hiroki Sayama


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The idea of creating artifacts that evolve by themselves has been at the heart of the Artificial Life research, dating back to the early motives of John von Neumann’s monumental work on self-reproducing automata in the 1940’s. This vein of research is unique and fundamentally different from other more widely studied evolutionary computation research, because basic processes of evolution (heredity, variation, selection) are not given a priori as built-in mechanisms but they need to emerge as a result of interactions among microscopic components. In this talk, I will provide a brief review of how this problem has been approached in ALife using various kinds of methodologies, including classic frameworks (e.g., cellular automata, evolving programs) and more modern ones (e.g., artificial chemistry, AI/ML). I aim to highlight several key ingredients in order for complex systems to show spontaneous evolutionary behaviors by themselves and, in particular, to exhibit open-ended exploration of the possibility space.

Watch at: www.youtube.com