Universal laws, architectures, and behaviors in effective understanding and action

John Doyle
California Institute of Technology
Control and Dynamical Systems

This talk will explore the problem of reasoning and understanding in the context of making decisions and performing actions. In organisms and evolution or machines and design, it is only actions that are ultimately the target of selection, though data processing, communication, and computation can play important roles in the process. The essential dimensions of this problem are the hard limits on what is achievable (laws), the organizing principles that succeed or fail in achieving them (architectures and protocols), and the resulting behavior observed in real systems (behavior, data).
Hard limits on measurement, prediction, communication, computation, decision, and control, as well as the underlying physical energy and material conversion mechanism necessary to implement these abstract process are at the heart of modern theories of systems in engineering and science (often associated with names such as Shannon, Poincare, Turing, Gödel, Bode, Wiener, Heisenberg, Carnot,…). They form the foundation for rich and deep subjects that are nevertheless now taught to undergraduates. Unfortunately, these subjects remain largely fragmented and incompatible, even as the tradeoffs between these limits are of growing importance in building integrated systems that go from data to action.
Insights into the universal laws, architecture, and organizational principles of such integrated systems can be drawn from three converging research themes. 1) With detailed description of components and a growing attention to systems biology and neuroscience, the organizational principles of organisms and evolution are becoming increasingly apparent. Biologists are articulating richly detailed explanations of biological complexity, robustness, and evolvability that point to universal principles and architectures. We will aim connect these insights with the role of layering, protocols, and feedback control in structuring complex multiscale modularity. 2) Advanced technology’s complexity is now approaching biology’s. While the components differ and the system processes are far less integrated, there are striking convergences at the level of organization and architecture. Determining what is essential about this convergence and what is merely historical accident requires a deeper understanding of architecture — the most universal, high-level, persistent elements of organization — and protocols. Protocols define how diverse modules interact, and architecture defines how sets of protocols are organized. 3) New mathematical frameworks for the study of complex networks suggests that this apparent network-level evolutionary convergence within/between biology/technology is not accidental, but follows necessarily from their universal system requirements to be fast, efficient, adaptive, evolvable, and robust to perturbations in their environment and component parts. The universal hard limits on systems and their components have until recently been studied separately in fragmented domains of physics, chemistry, biology, communications, computation, and control, but a unified theory is needed and appears feasible.

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