Edited by Jac C. Heckelman and Nicholas R. Miller
Chapter 5: Computational social choice
Computational social choice refers to a set of research areas found at the intersection of social choice theory and computer science. These research areas can be divided into three main categories, two of which will be discussed in detail in this chapter. The first is the use of computational tools to analyze, apply or extend traditional social choice models. One example is the use of ‘simulation experiments’ to explore the robustness of an existing social choice finding. Another example is the use of agent-based models to explore, test and experiment with complex social choice systems consisting of heterogeneous agents and multiple layers of social choice rules. The second major area of research in computational social choice is the application of computer science concepts to traditional issues within social choice. For instance, computer science concepts can be used to categorize voting rules based on their computational complexity or to examine communication complexity by measuring the amount of information that would need to be exchanged in a given social choice setting. Further, the computer science concept of knowledge representation is a useful tool for compactly representing preferences in highly combinatorial social choice scenarios.
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