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Academic literature on the topic 'Strategyproofne'

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Published: 11 March 2023

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Journal articles on the topic "Strategyproofne"

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Brandt, Felix, Martin Bullinger, and Patrick Lederer. "On the Indecisiveness of Kelly-Strategyproof Social Choice Functions." Journal of Artificial Intelligence Research 73 (April 1, 2022): 1093–130. http://dx.doi.org/10.1613/jair.1.13449.

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Social choice functions (SCFs) map the preferences of a group of agents over some set of alternatives to a non-empty subset of alternatives. The Gibbard-Satterthwaite theorem has shown that only extremely restrictive SCFs are strategyproof when there are more than two alternatives. For set-valued SCFs, or so-called social choice correspondences, the situation is less clear. There are miscellaneous -- mostly negative -- results using a variety of strategyproofness notions and additional requirements. The simple and intuitive notion of Kelly-strategyproofness has turned out to be particularly compelling because it is weak enough to still allow for positive results. For example, the Pareto rule is strategyproof even when preferences are weak, and a number of attractive SCFs (such as the top cycle, the uncovered set, and the essential set) are strategyproof for strict preferences. In this paper, we show that, for weak preferences, only indecisive SCFs can satisfy strategyproofness. In particular, (i) every strategyproof rank-based SCF violates Pareto-optimality, (ii) every strategyproof support-based SCF (which generalize Fishburn's C2 SCFs) that satisfies Pareto-optimality returns at least one most preferred alternative of every voter, and (iii) every strategyproof non-imposing SCF returns the Condorcet loser in at least one profile. We also discuss the consequences of these results for randomized social choice.
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Dhull, Komal, Steven Jecmen, Pravesh Kothari, and Nihar B. Shah. "Strategyproofing Peer Assessment via Partitioning: The Price in Terms of Evaluators’ Expertise." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 10, no. 1 (October 14, 2022): 53–63. http://dx.doi.org/10.1609/hcomp.v10i1.21987.

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Strategic behavior is a fundamental problem in a variety of real-world applications that require some form of peer assessment, such as peer grading of homeworks, grant proposal review, conference peer review of scientific papers, and peer assessment of employees in organizations. Since an individual's own work is in competition with the submissions they are evaluating, they may provide dishonest evaluations to increase the relative standing of their own submission. This issue is typically addressed by partitioning the individuals and assigning them to evaluate the work of only those from different subsets. Although this method ensures strategyproofness, each submission may require a different type of expertise for effective evaluation. In this paper, we focus on finding an assignment of evaluators to submissions that maximizes assigned evaluators' expertise subject to the constraint of strategyproofness. We analyze the price of strategyproofness: that is, the amount of compromise on the assigned evaluators' expertise required in order to get strategyproofness. We establish several polynomial-time algorithms for strategyproof assignment along with assignment-quality guarantees. Finally, we evaluate the methods on a dataset from conference peer review.
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Guo, Xiaoxi, Sujoy Sikdar, Lirong Xia, Yongzhi Cao, and Hanpin Wang. "Favoring Eagerness for Remaining Items: Designing Efficient, Fair, and Strategyproof Mechanisms." Journal of Artificial Intelligence Research 76 (January 21, 2023): 287–339. http://dx.doi.org/10.1613/jair.1.13878.

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In the assignment problem, the goal is to assign indivisible items to agents who have ordinal preferences, efficiently and fairly, in a strategyproof manner. In practice, first-choice maximality, i.e., assigning a maximal number of agents their top items, is often identified as an important efficiency criterion and measure of agents' satisfaction. In this paper, we propose a natural and intuitive efficiency property, favoring-eagerness-for-remaining-items (FERI), which requires that each item is allocated to an agent who ranks it highest among remaining items, thereby implying first-choice maximality. Using FERI as a heuristic, we design mechanisms that satisfy ex-post or ex-ante variants of FERI together with combinations of other desirable properties of efficiency (Pareto-efficiency), fairness (strong equal treatment of equals and sd-weak-envy-freeness), and strategyproofness (sd-weak-strategyproofness). We also explore the limits of FERI mechanisms in providing stronger efficiency, fairness, or strategyproofness guarantees through impossibility results.
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Brandt, Felix, and Christian Geist. "Finding Strategyproof Social Choice Functions via SAT Solving." Journal of Artificial Intelligence Research 55 (March 4, 2016): 565–602. http://dx.doi.org/10.1613/jair.4959.

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A promising direction in computational social choice is to address research problems using computer-aided proving techniques. In particular with SAT solvers, this approach has been shown to be viable not only for proving classic impossibility theorems such as Arrow's Theorem but also for finding new impossibilities in the context of preference extensions. In this paper, we demonstrate that these computer-aided techniques can also be applied to improve our understanding of strategyproof irresolute social choice functions. These functions, however, requires a more evolved encoding as otherwise the search space rapidly becomes much too large. Our contribution is two-fold: We present an efficient encoding for translating such problems to SAT and leverage this encoding to prove new results about strategyproofness with respect to Kelly's and Fishburn's preference extensions. For example, we show that no Pareto-optimal majoritarian social choice function satisfies Fishburn-strategyproofness. Furthermore, we explain how human-readable proofs of such results can be extracted from minimal unsatisfiable cores of the corresponding SAT formulas.
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Budish, Eric, and Estelle Cantillon. "The Multi-unit Assignment Problem: Theory and Evidence from Course Allocation at Harvard." American Economic Review 102, no. 5 (August 1, 2012): 2237–71. http://dx.doi.org/10.1257/aer.102.5.2237.

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We use theory and field data to study the draft mechanism used to allocate courses at Harvard Business School. We show that the draft is manipulable in theory, manipulated in practice, and that these manipulations cause significant welfare loss. Nevertheless, we find that welfare is higher than under its widely studied strategyproof alternative. We identify a new link between fairness and welfare that explains why the draft performs well despite the costs of strategic behavior, and then design a new draft that reduces these costs. We draw several broader lessons for market design, regarding Pareto efficiency, fairness, and strategyproofness. (JEL D63, D82, I23)
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Chida, Takafumi, Toshiya Kaihara, Nobutada Fujii, Daisuke Kokuryo, and Yuma Shiho. "Computational Study on Strategyproofness of Resource Matching in Crowdsourced Manufacturing." International Journal of Automation Technology 14, no. 5 (September 5, 2020): 734–43. http://dx.doi.org/10.20965/ijat.2020.p0734.

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The need for a sustainable society has grown rapidly. This trend requires new production system concepts following an era of mass customization. As one of these new concepts, “crowdsourced manufacturing” has attracted noticeable attention. In such systems, each participant shares their manufacturing resources for ecosystem co-prosperity, providing new value for the next society. To realize such a concept, it is important to (1) match resource requests and resource offers so as to achieve high efficiency, and (2) induce participants to act in a fair way. Previously, some studies showed production efficiency improvements. Nevertheless, relatively few studies have been conducted on induction mechanisms. The purpose of this study is to develop induction mechanisms for participants. Concerning induction mechanisms, we focus on two viewpoints: (a) matching stability, and (b) “strategyproofness.” These viewpoints are well-known concepts in the market design research field. We previously proposed a resource matching stability analysis method and mechanism for inducing participants to accept matching plans. Formally, a matching method is “strategyproof” when it is a dominant strategy for all participants to submit their true information. However, it is hard to satisfy this condition. Practically, it would be useful to evaluate the strength of an induction, even if the matching method is not strategyproof. In this study, we propose indices for showing the strength of induction (“strength of strategyproofness”). Subsequently, we evaluate matching methods, and show that participants will state false information to maximize their profit in a system with resource matching methods for the profit maximization of the entire system. As the resource providers, they can obtain greater profit by submitting false information regarding resource usage fees. Then, the profits of the resource requesters are unfairly impaired. Furthermore, we propose a new resource matching method, inspired from the “nucleolus” concept in cooperative game theory. The proposed method reduces the maximum dissatisfaction (i.e., profit loss) of resource requesters and resource providers, based on profit sharing. The computational results show that the proposed method induces participants to submit true information, while maintaining high production efficiency.
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Zou, James, Sujit Gujar, and David Parkes. "Tolerable Manipulability in Dynamic Assignment without Money." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (July 4, 2010): 947–52. http://dx.doi.org/10.1609/aaai.v24i1.7630.

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We study a problem of dynamic allocation without money. Agents have arrivals and departures and strict preferences over items. Strategyproofness requires the use of an arrival-priority serial-dictatorship (APSD) mechanism, which is ex post Pareto efficient but has poor ex ante efficiency as measured through average rank efficiency. We introduce the scoring-rule (SR) mechanism, which biases in favor of allocating items that an agent values above the population consensus. The SR mechanism is not strategyproof but has tolerable manipulability in the sense that: (i) if every agent optimally manipulates, it reduces to APSD, and (ii) it significantly outperforms APSD for rank efficiency when only a fraction of agents are strategic. The performance of SR is also robust to mistakes by agents that manipulate on the basis of inaccurate information about the popularity of items.
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Bichler, Martin, Zhen Hao, Richard Littmann, and Stefan Waldherr. "Strategyproof auction mechanisms for network procurement." OR Spectrum 42, no. 4 (July 25, 2020): 965–94. http://dx.doi.org/10.1007/s00291-020-00597-7.

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Abstract Deferred-acceptance auctions can be seen as heuristic algorithms to solve $${{\mathcal {N}}}{{\mathcal {P}}}$$ N P -hard allocation problems. Such auctions have been used in the context of the Incentive Auction by the US Federal Communications Commission in 2017, and they have remarkable incentive properties. Besides being strategyproof, they also prevent collusion among participants. Unfortunately, the worst-case approximation ratio of these algorithms is very low in general, but it was observed that they lead to near-optimal solutions in experiments on the specific allocation problem of the Incentive Auction. In this work, which is inspired by the telecommunications industry, we focus on a strategic version of the minimum Steiner tree problem, where the edges are owned by bidders with private costs. We design several deferred-acceptance auctions (DAAs) and compare their performance to the Vickrey–Clarke–Groves (VCG) mechanism as well as several other approximation mechanisms. We observe that, even for medium-sized inputs, the VCG mechanisms experiences impractical runtimes and that the DAAs match the approximation ratios of even the best strategy-proof mechanisms in the average case. We thus provide another example of an important practical mechanism design problem, where empirics suggest that carefully designed deferred-acceptance auctions with their superior incentive properties need not come at a cost in terms of allocative efficiency. Our experiments provide insights into the trade-off between solution quality and runtime and into the additional premium to be paid in DAAs to gain weak group-strategyproofness rather than just strategyproofness.
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Aziz, Haris, Hau Chan, Barton Lee, Bo Li, and Toby Walsh. "Facility Location Problem with Capacity Constraints: Algorithmic and Mechanism Design Perspectives." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 02 (April 3, 2020): 1806–13. http://dx.doi.org/10.1609/aaai.v34i02.5547.

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We consider the facility location problem in the one-dimensional setting where each facility can serve a limited number of agents from the algorithmic and mechanism design perspectives. From the algorithmic perspective, we prove that the corresponding optimization problem, where the goal is to locate facilities to minimize either the total cost to all agents or the maximum cost of any agent is NP-hard. However, we show that the problem is fixed-parameter tractable, and the optimal solution can be computed in polynomial time whenever the number of facilities is bounded, or when all facilities have identical capacities. We then consider the problem from a mechanism design perspective where the agents are strategic and need not reveal their true locations. We show that several natural mechanisms studied in the uncapacitated setting either lose strategyproofness or a bound on the solution quality %on the returned solution for the total or maximum cost objective. We then propose new mechanisms that are strategyproof and achieve approximation guarantees that almost match the lower bounds.
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Haeringer, Guillaume, and Hanna Hałaburda. "Monotone strategyproofness." Games and Economic Behavior 98 (July 2016): 68–77. http://dx.doi.org/10.1016/j.geb.2016.05.007.

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Dissertations / Theses on the topic "Strategyproofne"

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Leroux, Justin Theodore. "Essays on strategyproofness in cooperative production." Thesis, 2005. http://hdl.handle.net/1911/18852.

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We study incentive compatible profit-sharing rules when output (or profit) is obtained via the joint use of a technology exhibiting decreasing marginal returns. The incentives compatibility criterion we adopt is that of strategy-proofness (SP), arguably the most robust and the most demanding incentives requirement. We first show that no strategy-proof mechanism is efficient. We then characterize the class of strategy-proof mechanisms in the two-agent case, and show that it is the union of the serial and reverse serial families of sharing rules. Moreover, SP and the requirement that no individual benefits from the presence of others (the familiar stand-alone test) characterize the class of rules known as fixed path methods (FPMs), which is a subset of the serial family. FPMs share marginal increments of input, and the corresponding increments of output, along a predetermined path. Finally, we consider a situation where a number of individuals form a partnership and contribute capital and labor to the enterprise. We propose a strategy-proof mechanism which improves upon autarky: the inverse marginal product proportions (IMPP) mechanism. At the margin, capital that would be left idle in autarky, but not under the efficient use of the total capital, is assigned to the agents with relatively low disutility of effort in proportion to the relative productivity of their own capital. The IMPP mechanism is effectively an FPM whose path is uniquely determined by the capital contributions of the partners. Thus, we establish a correspondence between the class of FPMs to manage a common property technology and the family of partnership problems. We discuss the appeal of the IMPP mechanism as an alternative to existing profit-sharing schemes in professional partnerships.
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Book chapters on the topic "Strategyproofne"

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Chun, Youngsub. "Strategyproofness." In Studies in Choice and Welfare, 61–78. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33771-5_6.

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Kao, Ming-Yang. "Strategyproof." In Encyclopedia of Algorithms, 906. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_405.

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Morrill, Thayer. "Beyond Strategyproofness." In The Future of Economic Design, 483–84. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18050-8_68.

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Chun, Youngsub. "Strategyproofness and Egalitarian Equivalence." In Studies in Choice and Welfare, 79–92. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33771-5_7.

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Ferraioli, Diodato, and Carmine Ventre. "Obvious Strategyproofness, Bounded Rationality and Approximation." In Algorithmic Game Theory, 77–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30473-7_6.

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Meir, Reshef. "Strategyproofness and the Gibbard-Satterthwaite Theorem." In Strategic Voting, 15–28. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-01579-3_3.

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Fotakis, Dimitris, and Panagiotis Patsilinakos. "Strategyproof Facility Location in Perturbation Stable Instances." In Web and Internet Economics, 95–112. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94676-0_6.

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Gopinathan, Ajay, and Zongpeng Li. "Strategyproof Mechanisms for Content Delivery via Layered Multicast." In NETWORKING 2011, 82–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20798-3_7.

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Immorlica, Nicole, and Emmanouil Pountourakis. "On Budget-Balanced Group-Strategyproof Cost-Sharing Mechanisms." In Lecture Notes in Computer Science, 244–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35311-6_18.

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Xu, Ping, and Xiang-Yang Li. "SOFA: Strategyproof Online Frequency Allocation for Multihop Wireless Networks." In Algorithms and Computation, 311–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10631-6_33.

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Conference papers on the topic "Strategyproofne"

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Lederer, Patrick. "Strategyproof Randomized Social Choice for Restricted Sets of Utility Functions." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/43.

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When aggregating preferences of multiple agents, strategyproofness is a fundamental requirement. For randomized voting rules, so-called social decision schemes (SDSs), strategyproofness is usually formalized with the help of utility functions. A classic result shown by Gibbard in 1977 characterizes the set of SDSs that are strategyproof with respect to all utility functions and shows that these SDSs are either indecisive or unfair. For finding more insights into the trade-off between strategyproofness and decisiveness, we propose the notion of U-strategyproofness which requires that only voters with a utility function in the set U cannot manipulate. In particular, we show that if the utility functions in U value the best alternative much more than other alternatives, there are U-strategyproof SDSs that choose an alternative with probability 1 whenever all but k voters rank it first. We also prove for rank-based SDSs that this large gap in the utilities is required to be strategyproof and that the gap must increase in k. On the negative side, we show that U-strategyproofness is incompatible with Condorcet-consistency if U satisfies minimal symmetry conditions and there are at least four alternatives. For three alternatives, the Condorcet rule can be characterized based on U-strategyproofness for the set U containing all equi-distant utility functions.
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Menon, Vijay, and Kate Larson. "Deterministic, Strategyproof, and Fair Cake Cutting." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/50.

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We study the classic cake cutting problem from a mechanism design perspective, in particular focusing on deterministic mechanisms that are strategyproof and fair. We begin by looking at mechanisms that are non-wasteful and primarily show that for even the restricted class of piecewise constant valuations there exists no direct-revelation mechanism that is strategyproof and even approximately proportional. Subsequently, we remove the non-wasteful constraint and show another impossibility result stating that there is no strategyproof and approximately proportional direct-revelation mechanism that outputs contiguous allocations, again, for even the restricted class of piecewise constant valuations. In addition to the above results, we also present some negative results when considering an approximate notion of strategyproofness, show a connection between direct-revelation mechanisms and mechanisms in the Robertson-Webb model when agents have piecewise constant valuations, and finally also present a (minor) modification to the well-known Even-Paz algorithm that has better incentive-compatible properties for the cases when there are two or three agents.
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Li, Minming, Pinyan Lu, Yuhao Yao, and Jialin Zhang. "Strategyproof Mechanism for Two Heterogeneous Facilities with Constant Approximation Ratio." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/34.

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In this paper, we study the two-facility location game with optional preference where the acceptable set of facilities for each agent could be different and an agent's cost is his distance to the closest facility within his acceptable set. The objective is to minimize the total cost of all agents while achieving strategyproofness. For general metrics, we design a deterministic strategyproof mechanism for the problem with approximation ratio of 1+2alpha, where alpha is the approximation ratio of the optimization version. In particular, for the setting on a line, we improve the earlier best ratio of n/2+1 to a ratio of 2.75.
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Xu, Yichong, Han Zhao, Xiaofei Shi, and Nihar B. Shah. "On Strategyproof Conference Peer Review." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/87.

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We consider peer review under a conference setting where there are conflicts between the reviewers and the submissions. Under such conflicts, reviewers can manipulate their reviews in a strategic manner to influence the final rankings of their own papers. Present-day peer-review systems are not designed to guard against such strategic behavior, beyond minimal (and insufficient) checks such as not assigning a paper to a conflicted reviewer. In this work, we address this problem through the lens of social choice, and present a theoretical framework for strategyproof and efficient peer review. Given the conflict graph which satisfies a simple property, we first present and analyze a flexible framework for reviewer-assignment and aggregation for the reviews that guarantees not only strategyproofness but also a natural efficiency property (unanimity). Our framework is based on the so-called partitioning method, and can be treated as a generalization of this type of method to conference peer review settings. We then empirically show that the requisite property on the (authorship) conflict graph is indeed satisfied in the ICLR-17 submissions data, and further demonstrate a simple trick to make the partitioning method more practically appealing under conference peer-review settings. Finally, we complement our positive results with negative theoretical results where we prove that under slightly stronger requirements, it is impossible for any algorithm to be both strategyproof and efficient.
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Brandt, Felix, Patrick Lederer, and Warut Suksompong. "Incentives in Social Decision Schemes with Pairwise Comparison Preferences." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/19.

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Social decision schemes (SDSs) map the preferences of individual voters over multiple alternatives to a probability distribution over the alternatives. In order to study properties such as efficiency, strategyproofness, and participation for SDSs, preferences over alternatives are typically lifted to preferences over lotteries using the notion of stochastic dominance (SD). However, requiring strategyproofness or strict participation with respect to this preference extension only leaves room for rather undesirable SDSs such as random dictatorships. Hence, we focus on the natural but little understood pairwise comparison (PC) preference extension, which postulates that one lottery is preferred to another if the former is more likely to return a preferred outcome. In particular, we settle three open questions raised by Brandt in Rolling the dice: Recent results in probabilistic social choice (2017): (i) there is no Condorcet-consistent SDS that satisfies PC-strategyproofness; (ii) there is no anonymous and neutral SDS that satisfies PC-efficiency and PC-strategyproofness; and (iii) there is no anonymous and neutral SDS that satisfies PC-efficiency and strict PC-participation. All three impossibilities require m>=4 alternatives and turn into possibilities when m<=3.
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Varloot, Estelle Marine, and Rida Laraki. "Level-strategyproof Belief Aggregation Mechanisms." In EC '22: The 23rd ACM Conference on Economics and Computation. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3490486.3538309.

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Gopinathan, Ajay, and Zongpeng Li. "Strategyproof Wireless Spectrum Auctions with Interference." In GLOBECOM 2010 - 2010 IEEE Global Communications Conference. IEEE, 2010. http://dx.doi.org/10.1109/glocom.2010.5684075.

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Wang, Jiafan, and Sherman S. M. Chow. "Secure Strategyproof Ascending-Price Spectrum Auction." In 2017 IEEE Symposium on Privacy-Aware Computing (PAC). IEEE, 2017. http://dx.doi.org/10.1109/pac.2017.42.

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Ferraioli, Diodato, and Carmine Ventre. "Probabilistic Verification for Obviously Strategyproof Mechanisms." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/33.

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Obviously strategyproof (OSP) mechanisms maintain the incentive compatibility of agents that are not fully rational. They have been object of a number of studies since their recent definition. A research agenda, initiated in [Ferraioli and Ventre, 2017], is to find a small set (possibly, the smallest) of conditions allowing to implement an OSP mechanism. To this aim, we define a model of probabilistic verification wherein agents are caught misbehaving with a certain probability, and show how OSP mechanisms can implement every social choice function at the cost of either imposing very large fines or verifying a linear number of agents.
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Chen, Yiling, Chara Podimata, Ariel D. Procaccia, and Nisarg Shah. "Strategyproof Linear Regression in High Dimensions." In EC '18: ACM Conference on Economics and Computation. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3219166.3219175.

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