Law as Data: Computation, Text, and the Future of Legal Analysis (Seminar) | Worlds Hidden in Plain Sight: Thirty Years of Complexity Thinking at the Santa Fe Institute (Compass) | Algorithms Illuminated (Part 3): Greedy Algorithms and Dynamic Programming | Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning | The Elements of Thinking in Systems: Use Systems Archetypes to Understand, Manage, and Fix Complex Problems and Make Smarter Decisions | Networks | Model Thinker: What You Need to Know to Make Data Work for You
The quantitative tools and concepts needed to understand the co-evolutionary nature of networked systems and their properties are challenging. The book gives a self-contained introduction to these concepts, so that the reader will be equipped with a toolset that allows them to engage in the science of complex systems. Topics covered include random processes of path-dependent processes, co-evolutionary dynamics, dynamics of networks, the theory of scaling, and approaches from statistical mechanics and information theory. The book extends beyond the early classical literature in the field of complex systems and summarizes the methodological progress made over the past 20 years in a clear, structured, and comprehensive way.
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