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Tri :   Date Editeur Auteur Titre

Decision making at scale: Algorithms, Mechanisms, and Platforms

/ INRIA (Institut national de recherche en informatique et automatique), CNRS - Centre National de la Recherche Scientifique, UNS, Région PACA / 16-06-2016 / Canal-u.fr
Goel Ashish
Voir le résumé
Voir le résumé
YouTube competes with Hollywood as an entertainment channel, and also supplements Hollywood by acting as a distribution mechanism. Twitter has a similar relationship to news media, and Coursera to Universities. But there are no online alternatives for making democratic decisions at large scale as a society. In this talk, we will describe two algorithmic approaches towards large scale decision making that we are exploring. a) Knapsack voting and participatory budgeting: All budget problems are knapsack problems at their heart, since the goal is to pack the largest amount of societal value into a budget. This naturally leads to « knapsack voting » where each voter solves a knapsack problem, or comparison-based voting where each voter compares pairs of projects in terms of benefit-per-dollar. We analyze natural aggregation algorithms for these mechanisms, and show that knapsack voting is strategy-proof. We will also describe our experience with helping implement participatory budgeting in close to two dozen cities and municipalities, and briefly comment on issues of fairness. b) Triadic consensus: Here, we divide individuals into small groups (say groups of three) and ask them to come to consensus; the results of the triadic deliberations in each round form the input to the next round. We show that this method is efficient and strategy-proof in fairly general settings, whereas no pair-wise deliberation process can have the same properties. This is joint work with Tanja Aitamurto, Brandon Fain, Anilesh Krishnaswamy, David Lee, Kamesh Munagala, and Sukolsak Sakshuwong. Bio:
Mot(s) clés libre(s) : problème knapsack, triadic consensus
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