Iterative deliberation via metric aggregation. (English) Zbl 07670905
Fotakis, Dimitris (ed.) et al., Algorithmic decision theory. 7th international conference, ADT 2021, Toulouse, France, November 3–5, 2021. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 13023, 162-176 (2021).
Summary: We investigate an iterative deliberation process for an agent community wishing to make a joint decision. We develop a general model consisting of a community of \(n\) agents, each with their initial ideal point in some metric space \((X, d)\), such that in each iteration of the iterative deliberation process, all agents move slightly closer to the current winner, according to some voting rule \(\mathcal{R}\). For several natural metric spaces and suitable voting rules for them, we identify conditions under which such an iterative deliberation process is guaranteed to converge.
For the entire collection see [Zbl 1507.91003].
For the entire collection see [Zbl 1507.91003].
MSC:
| 68T20 | Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) |
| 91B06 | Decision theory |
| 91B14 | Social choice |
| 91B32 | Resource and cost allocation (including fair division, apportionment, etc.) |
| 91B68 | Matching models |
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