Chaos in Dynamical Systems and Predictability

J. Doyne Farmer is the Director of the Complexity Economics programme at the Institute for New Economic Thinking at the Oxford Martin School, a Professor at the Mathematical Institute of Oxford University, and an External Professor at the Santa Fe Institute.

In this episode, we explore Doyne’s latest book, “Making Sense of Chaos.” We focus on the relationship between chaos and scaling theory, and more specifically, how chaos can be factored into scaling theory. By the end of this conversation, you will learn why it might be easier to predict the long distant future than predicting tomorrow, how Moore’s Law conflicts with other scaling laws that underpin technological progress, how agent-based modeling can help all scientists and policymakers, how to dominate the world with your theories (...), and even how to trick casinos. I hope you enjoy the conversation.

Find me on X at @⁠⁠ProfSchrepel⁠⁠. Also, be sure to subscribe to the Scaling Theory podcast; it helps its growth.

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