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We study the problem of learning Markov decision processes with finite state and action spaces when the transition probability distributions and loss functions are chosen adversarially and are allowed to change with time. We introduce an…

Machine Learning · Computer Science 2013-03-14 Yasin Abbasi-Yadkori , Peter L. Bartlett , Csaba Szepesvari

Large language models increasingly rely on explicit reasoning chains and can produce multiple plausible responses for a given context. We study the candidate sampler that produces the set of plausible responses contrasting the ancestral…

Computation and Language · Computer Science 2025-09-23 Sergey Troshin , Irina Saparina , Antske Fokkens , Vlad Niculae

Citizens' assemblies are a form of democratic innovation in which a randomly selected panel of constituents deliberates on questions of public interest. We study a novel goal for the selection of panel members: maximizing the entropy of the…

Computer Science and Game Theory · Computer Science 2026-04-06 Gabriel de Azevedo , Paul Gölz

Over the past decade it has become evident that intentional disinformation in the political context -- so-called fake news -- is a danger to democracy. However, until now there has been no clear understanding of how to define fake news,…

Applications · Statistics 2021-12-01 Dorje C. Brody , David M. Meier

In this paper, we present a novel fraud-proof mechanism that achieves fast finality and, when combined with optimistic execution, enables real-time transaction processing. State-of-the-art optimistic rollups typically adopt a 7-day…

Cryptography and Security · Computer Science 2025-02-17 Gabriele Picco , Andrea Fortugno

Much of the theoretical work on strategic voting makes strong assumptions about what voters know about the voting situation. A strategizing voter is typically assumed to know how other voters will vote and to know the rules of the voting…

Multiagent Systems · Computer Science 2019-07-23 Wesley H. Holliday , Eric Pacuit

We study multiwinner elections with approval-based preferences. An instance of a multiwinner election consists of a set of alternatives, a population of voters---each voter approves a subset of alternatives, and the desired committee size…

Computer Science and Game Theory · Computer Science 2019-10-15 Piotr Skowron

We report the "Recurrent Deterioration" (RD) phenomenon observed in online recommender systems. The RD phenomenon is reflected by the trend of performance degradation when the recommendation model is always trained based on users' feedbacks…

Artificial Intelligence · Computer Science 2016-09-02 Zhongqi Lu , Qiang Yang

We consider the computational complexity of a problem modeling bribery in the context of voting systems. In the scenario of Swap Bribery, each voter assigns a certain price for swapping the positions of two consecutive candidates in his…

Computational Complexity · Computer Science 2015-05-20 Britta Dorn , Ildikó Schlotter

General purpose intelligent learning agents cycle through (complex,non-MDP) sequences of observations, actions, and rewards. On the other hand, reinforcement learning is well-developed for small finite state Markov Decision Processes…

Artificial Intelligence · Computer Science 2009-12-30 Marcus Hutter

Motivated by information sharing in online platforms, we study repeated persuasion between a sender and a stream of receivers where at each time, the sender observes a payoff-relevant state drawn independently and identically from an…

Computer Science and Game Theory · Computer Science 2024-05-06 You Zu , Krishnamurthy Iyer , Haifeng Xu

The executive branch, or government, is typically not elected directly by the people, but rather formed by another elected body or person such as the parliament or the president. As a result, its members are not directly accountable to the…

Multiagent Systems · Computer Science 2023-12-11 Rutvik Page , Ehud Shapiro , Nimrod Talmon

The outcomes of democratic elections rest on individuals' decision-making that is driven by their varying preferences and beliefs. Individuals may prefer consensus to gridlock, or gridlock to consensus, and information may be fractured via…

Physics and Society · Physics 2024-10-29 Jonathan Engle , Bryce Morsky

We study elections where voters are faced with the challenge of expressing preferences over an extreme number of issues under consideration. This is largely motivated by emerging blockchain governance systems, which include voters with…

Computer Science and Game Theory · Computer Science 2024-05-15 Georgios Amanatidis , Aris Filos-Ratsikas , Philip Lazos , Evangelos Markakis , Georgios Papasotiropoulos

Multi-agent debate (MAD) is an emerging approach to improving the reasoning capabilities of large language models (LLMs). Existing MAD methods rely on multiple rounds of interaction among agents to reach consensus, and the final output is…

Artificial Intelligence · Computer Science 2025-09-16 Yu Cui , Hang Fu , Haibin Zhang , Licheng Wang , Cong Zuo

Voting methods are instrumental design elements of democracies. Citizens use them to express and aggregate their preferences to reach a collective decision. However, voting outcomes can be as sensitive to voting rules as they are to…

The outcome of elections is strongly dependent on the districting choices, making thus possible (and frequent) the gerrymandering phenomenon, i.e.\ politicians suitably changing the shape of electoral districts in order to win the…

Optimization and Control · Mathematics 2019-10-22 Alberto Saracco , Giorgio Saracco

When building recommendation systems, we seek to output a helpful set of items to the user. Under the hood, a ranking model predicts which of two candidate items is better, and we must distill these pairwise comparisons into the user-facing…

Information Retrieval · Computer Science 2022-07-05 Anastasios N. Angelopoulos , Karl Krauth , Stephen Bates , Yixin Wang , Michael I. Jordan

Many democratic political parties hold primary elections, which nicely reflects their democratic nature and promote, among other things, the democratic value of inclusiveness. However, the methods currently used for holding such primary…

Multiagent Systems · Computer Science 2022-01-20 Ariel Rosenfeld , Ehud Shapiro , Nimrod Talmon

The strongest threat model for voting systems considers coercion resistance: protection against coercers that force voters to modify their votes, or to abstain. Existing remote voting systems either do not provide this property; require an…

Cryptography and Security · Computer Science 2020-06-02 Wouter Lueks , Iñigo Querejeta-Azurmendi , Carmela Troncoso