Convincing Features
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INTRODUCTION
Computational social choice exploits the idea that any mechanism we may use to make collective decisions is ultimately an algorithm. Thus, many techniques developed in computer science greatly contributed to the field. Computational complexity is a beautiful example as it allows for an informed discussion about such mechanisms:
For example by studying the hardness of computing an outcome or by acting as a barrier against manipulation. Logic and knowledge representation has been used to study the compact representation of preferences and to develop voting in combinatorial domains. Many more examples are reviewed in the Handbook of Computational Social Choice
JUSTIFYING COLLECTIVE DECISIONS
As the first step in this direction, I will now present how the availability of computer-aided methods can help us to reason about the possible outcomes of a collective making decision process. This section is based on the notion of justification developed in a recent paper co-written with Endriss in which we extend the work of Cailloux and Endriss.
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