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Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about uncertainty and multi-agent systems. When the set of agents and the set…

Computer Science and Game Theory · Computer Science 2012-07-19 Moshe Tennenholtz

In a real expert system, one may have unreliable, unconfident, conflicting estimates of the value for a particular parameter. It is important for decision making that the information present in this aggregate somehow find its way into use.…

Artificial Intelligence · Computer Science 2013-04-15 Henry Hamburger

A ranking is an ordered sequence of items, in which an item with higher ranking score is more preferred than the items with lower ranking scores. In many information systems, rankings are widely used to represent the preferences over a set…

Artificial Intelligence · Computer Science 2017-09-22 Zhiwei Lin , Yi Li , Xiaolian Guo

We consider methods for aggregating preferences that are based on the resolution of discrete optimization problems. The preferences are represented by arbitrary binary relations (possibly weighted) or incomplete paired comparison matrices.…

Optimization and Control · Mathematics 2007-05-23 Pavel Chebotarev , Elena Shamis

Argumentation is a process of evaluating and comparing a set of arguments. A way to compare them consists in using a ranking-based semantics which rank-order arguments from the most to the least acceptable ones. Recently, a number of such…

Artificial Intelligence · Computer Science 2016-02-03 Elise Bonzon , Jérôme Delobelle , Sébastien Konieczny , Nicolas Maudet

We introduce a framework for benchmarking optimizers according to multiple criteria over various test functions. Based on a recently introduced union-free generic depth function for partial orders/rankings, it fully exploits the ordinal…

Machine Learning · Computer Science 2024-09-09 Julian Rodemann , Hannah Blocher

Ranking functions that are used in decision systems often produce disparate results for different populations because of bias in the underlying data. Addressing, and compensating for, these disparate outcomes is a critical problem for fair…

Machine Learning · Computer Science 2024-04-23 Abraham Gale , Amélie Marian

Journal ranking is becoming more important in assessing the quality of academic research. Several indices have been suggested for this purpose, typically on the basis of a citation graph between the journals. We follow an axiomatic approach…

Digital Libraries · Computer Science 2020-05-28 László Csató

Reputation is crucial to enabling human or software agents to select among alternative providers. Although several effective reputation assessment methods exist, they typically distil reputation into a numerical representation, with no…

Artificial Intelligence · Computer Science 2020-06-17 Ingrid Nunes , Phillip Taylor , Lina Barakat , Nathan Griffiths , Simon Miles

Pairwise comparisons between alternatives are a well-established tool to decompose decision problems into smaller and more easily tractable sub-problems. However, due to our limited rationality, the subjective preferences expressed by…

Artificial Intelligence · Computer Science 2016-03-15 Matteo Brunelli

Given a set of conflicting arguments, there can exist multiple plausible opinions about which arguments should be accepted, rejected, or deemed undecided. We study the problem of how multiple such judgments can be aggregated. We define the…

Artificial Intelligence · Computer Science 2017-06-20 Edmond Awad , Richard Booth , Fernando Tohme , Iyad Rahwan

An important problem in decision theory concerns the aggregation of individual rankings/ratings into a collective evaluation. We illustrate a new aggregation method in the context of the 2007 MSOM's student paper competition. The…

Artificial Intelligence · Computer Science 2021-01-14 Dorit S. Hochbaum , Erick Moreno-Centeno

We propose a novel and efficient algorithm for the collaborative preference completion problem, which involves jointly estimating individualized rankings for a set of entities over a shared set of items, based on a limited number of…

Machine Learning · Statistics 2016-11-16 Suriya Gunasekar , Oluwasanmi Koyejo , Joydeep Ghosh

Rank aggregation systems collect ordinal preferences from individuals to produce a global ranking that represents the social preference. Rank-breaking is a common practice to reduce the computational complexity of learning the global…

Machine Learning · Computer Science 2016-10-10 Ashish Khetan , Sewoong Oh

Rankings of people and items has been highly used in selection-making, match-making, and recommendation algorithms that have been deployed on ranging of platforms from employment websites to searching tools. The ranking position of a…

Social and Information Networks · Computer Science 2021-03-03 Akrati Saxena , George Fletcher , Mykola Pechenizkiy

Evaluating performance across optimization algorithms on many problems presents a complex challenge due to the diversity of numerical scales involved. Traditional data processing methods, such as hypothesis testing and Bayesian inference,…

Optimization and Control · Mathematics 2024-09-10 Yunpeng Jinng , Qunfeng Liu

Reaching some form of consensus is often necessary for autonomous agents that want to coordinate their actions or otherwise engage in joint activities. One way to reach a consensus is by aggregating individual information, such as…

Multiagent Systems · Computer Science 2016-07-13 Marija Slavkovik

A primary challenge in collective decision-making is that achieving unanimous agreement is difficult, even at the level of criteria. The history of social choice theory illustrates this: numerous normative criteria on voting rules have been…

Theoretical Economics · Economics 2026-01-23 Takahiro Suzuki , Stefano Moretti , Michele Aleandri

Eliciting relevance judgments for ranking evaluation is labor-intensive and costly, motivating careful selection of which documents to judge. Unlike traditional approaches that make this selection deterministically, probabilistic sampling…

Information Retrieval · Computer Science 2016-04-26 Tobias Schnabel , Adith Swaminathan , Peter Frazier , Thorsten Joachims

There is an innate human tendency, one might call it the "league table mentality," to construct rankings. Schools, hospitals, sports teams, movies, and myriad other objects are ranked even though their inherent multi-dimensionality would…

Econometrics · Economics 2021-09-16 Jiaying Gu , Roger Koenker