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Tanvi Namjoshi

dblp:371/4166 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0003-1311-4111ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design
evolutionary game theory
0.912025
Replicating Electoral Success · AAAI 2025
Algorithmic game theory and mechanism design › social choice › voting
plurality voting
0.912025
Replicating Electoral Success · AAAI 2025
Algorithmic game theory and mechanism design › evolutionary game theory
replicator dynamics
0.912025
Replicating Electoral Success · AAAI 2025

Methods — techniques the papers use, named apart from their topics

replicator dynamics · 0.9bounded rationality · 0.9
YearPublicationVenuePosition
2025 Replicating Electoral Success
abstract
A core tension in the study of plurality elections is the clash between the classic Hotelling-Downs model, which predicts that two office-seeking candidates should cater to the median voter, and the empirical observation that democracies often have two major parties with divergent policies. Motivated in part by this tension, we introduce a dynamic model of candidate positioning based on a simple bounded rationality heuristic: candidates imitate the policy of previous winners. The resulting model is closely connected to evolutionary replicator dynamics. For uniformly-distributed voters, we prove in our model that with k = 2, 3, or 4 candidates per election, any symmetric candidate distribution converges over time to the center. With k ≥ 5 candidates per election, however, we prove that the candidate distribution does not converge to the center and provide an even stronger non-convergence result in a special case with no extreme candidates. Our conclusions are qualitatively unchanged if a small fraction of candidates are not winner-copiers and are instead positioned uniformly at random in each election. Beyond our theoretical analysis, we illustrate our results in extensive simulations; for five or more candidates, we find a tendency towards the emergence of two clusters, a mechanism suggestive of Duverger's Law, the empirical finding that plurality leads to two-party systems. Our simulations also explore several variations of the model, where we find the same general pattern: convergence to the center with four or fewer candidates, but not with five or more. Finally, we discuss the relationship between our replicator dynamics model and prior work on strategic equilibria of candidate positioning games.
Kiran Tomlinson, Tanvi Namjoshi, Johan Ugander, Jon M. Kleinberg
AAAI2