In this lecture, we discuss topics related to "Prospects of Computer Modeling" by Mitchell (2009, Chapter 14). We start with a discussion of what it means for complex systems science to be a science. We follow that with a re-introduction to the scientific process, where we make things like causal questions, hypotheses, experiments, models, predictions, and theories explicit. We focus a lot on how hypotheses are answers to causal how/why questions and are NOT if–then statements (which are predictions). After going through the scientific process, we introduce the computational social simulation of the evolution of cooperation (starting with Robert Axelrod's popular efforts) and the prisoner's dilemma model. We do not quite get to the main computational results from Axelrod's study, which we will touch on at the start of the next lecture. We do discuss the requirements for a game to be a prisoner's dilemma and how the Nash equilibrium of the prisoner's dilemma is not Pareto efficient, which makes it a good model for such traps as the tragedy of the commons.
Whiteboard lecture notes for this lecture can be found at: https://www.dropbox.com/s/uq67nzc2nur27r6/SOS220-LectureH1-2023-04-06-Computational_Social_Simulation.pdf?dl=0
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