Average-Case Analysis of Iterative Voting

Iterative voting is a natural model of repeated strategic decision-making in social choice when agents have the opportunity to update their votes prior to finalizing the group decision. Prior work has analyzed the efficacy of iterative plurality on the welfare of the chosen outcome at equilibrium, relative to the truthful vote profile, via an adaptation of the price of anarchy. However, prior analyses have only studied the worst- and average-case performances when agents' preferences are distributed by the impartial culture. This work extends average-case analysis to a wider class of distributions and distinguishes when iterative plurality improves or degrades asymptotic welfare.Comment: 75 pages, 2 figure

Strategic Behavior is Bliss: Iterative Voting Improves Social Welfare

Recent work in iterative voting has defined the additive dynamic price of anarchy (ADPoA) as the difference in social welfare between the truthful and worst-case equilibrium profiles resulting from repeated strategic manipulations. While iterative plurality has been shown to only return alternatives with at most one less initial votes than the truthful winner, it is less understood how agents' welfare changes in equilibrium. To this end, we differentiate agents' utility from their manipulation mechanism and determine iterative plurality's ADPoA in the worst- and average-cases. We first prove that the worst-case ADPoA is linear in the number of agents. To overcome this negative result, we study the average-case ADPoA and prove that equilibrium winners have a constant order welfare advantage over the truthful winner in expectation. Our positive results illustrate the prospect for social welfare to increase due to strategic manipulation.Comment: 21 pages, 5 figures, in NeurIPS 202

Convergence of Multi-Issue Iterative Voting under Uncertainty

We study the effect of strategic behavior in iterative voting for multiple issues under uncertainty. We introduce a model synthesizing simultaneous multi-issue voting with Meir, Lev, and Rosenschein (2014)'s local dominance theory and determine its convergence properties. After demonstrating that local dominance improvement dynamics may fail to converge, we present two sufficient model refinements that guarantee convergence from any initial vote profile for binary issues: constraining agents to have O-legal preferences and endowing agents with less uncertainty about issues they are modifying than others. Our empirical studies demonstrate that although cycles are common when agents have no uncertainty, introducing uncertainty makes convergence almost guaranteed in practice.Comment: 19 pages, 4 figure

Hide, Not Seek: Perceived Fairness in Envy-Free Allocations of Indivisible Goods

Fair division provides a rich computational and mathematical framework for the allocation of indivisible goods, which has given rise to numerous fairness concepts and their relaxations. In recent years, much attention has been given to theoretical and computational aspects of various fairness concepts. Nonetheless, the choice of which fairness concept is in practice perceived to be fairer by individuals is not well understood. We consider two conceptually different relaxations of envy-freeness and investigate how individuals perceive the induced allocations as fair. In particular, we examine a well-studied relaxation of envy-freeness up to one good (EF1) which is based on counterfactual thinking that any pairwise envy can be eliminated by the hypothetical removal of a single good from the envied agent's bundle. In contrast, a recently proposed epistemic notion, namely envy-freeness up to $k$ hidden goods (HEF-$k$), provides a relaxation by hiding information about a small subset of $k$ goods. Through various crowdsourcing experiments, we empirically demonstrate that allocations achieved by withholding information are perceived to be fairer compared to two variants of EF1.Comment: 21 pages, 10 figure

First results from a search for coherent elastic neutrino-nucleus scattering at a reactor site

The deployment of a low-noise 3 kg p-type point contact germanium detector at the Dresden-II power reactor, 8 meters from its $2.96  GW_{th}$ core, is described. This location provides an unprecedented (anti)neutrino flux of $8.1×10^{13}  \overline{v_e}/cm^2s$. When combined with the $0.2  keV_{ee}$ detector threshold achieved, a first measurement of $CE⁢⁢NS$ from a reactor source appears to be within reach. We report on the characterization and abatement of backgrounds during initial runs, deriving improved limits on extensions of the Standard Model involving a light vector mediator, from preliminary data

Philosophy of Science, Network Theory, and Conceptual Change: Paradigm Shifts as Information Cascades

Philosophers have long tried to understand scientific change in terms of a dynamics of revision within ‘theoretical frameworks,’ ‘disciplinary matrices,’ ‘scientific paradigms’ or ‘conceptual schemes.’ No-one, however, has made clear precisely how one might model such a conceptual scheme, nor what form change dynamics within such a structure could be expected to take. In this paper we take some first steps in applying network theory to the issue, modeling conceptual schemes as simple networks and the dynamics of change as cascades on those networks. The results allow a new understanding of two traditional approaches—Popper and Kuhn—as well as introducing the intriguing prospect of viewing scientific change using the metaphor of selforganizing criticality