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Fairness in multiwinner elections is studied in varying contexts. For instance, diversity of candidates and representation of voters are both separately termed as being fair. A common denominator to ensure fairness across all such contexts…

Computer Science and Game Theory · Computer Science 2022-11-24 Kunal Relia

Quantum entanglement has been recently demonstrated as a useful resource in conflicting interest games of incomplete information between two players, Alice and Bob [Pappa et al., Phys. Rev. Lett. 114, 020401 (2015)]. General setting for…

Quantum Physics · Physics 2017-11-17 Ashutosh Rai , Goutam Paul

This article studies a general divide-and-conquer algorithm for approximating continuous one-dimensional probability distributions with finite mean. The article presents a numerical study that compares pre-existing approximation schemes…

We consider the problem of designing an expected-revenue maximizing mechanism for allocating multiple non-perishable goods of $k$ varieties to flexible consumers over $T$ time steps. In our model, a random number of goods of each variety…

Computer Science and Game Theory · Computer Science 2020-07-08 Shiva Navabi , Ashutosh Nayyar

Inspired by Internet ad auction applications, we study the problem of allocating a single item via an auction when bidders place very different values on the item. We formulate this as the problem of prior-free auction and focus on…

Computer Science and Game Theory · Computer Science 2009-09-30 Vahab Mirrokni , S. Muthukrishnan , Uri Nadav

In this article we propose a probabilistic framework in order to study the fair division of a divisible good, e.g., a cake, between n players. Our framework follows the same idea than the ''Full independence model'' used in the study of…

Computational Complexity · Computer Science 2021-08-25 Guillaume Chèze

The game-theoretic risk management framework put forth in the precursor work "Towards a Theory of Games with Payoffs that are Probability-Distributions" (arXiv:1506.07368 [q-fin.EC]) is herein extended by algorithmic details on how to…

General Economics · Economics 2020-04-10 Stefan Rass

We study the voting game where agents' preferences are endogenously decided by the information they receive, and they can collaborate in a group. We show that strategic voting behaviors have a positive impact on leading to the ``correct''…

Computer Science and Game Theory · Computer Science 2023-05-23 Qishen Han , Grant Schoenebeck , Biaoshuai Tao , Lirong Xia

We consider a setting where $n$ buyers, with combinatorial preferences over $m$ items, and a seller, running a priority-based allocation mechanism, repeatedly interact. Our goal, from observing limited information about the results of these…

Computer Science and Game Theory · Computer Science 2014-08-29 Avrim Blum , Yishay Mansour , Jamie Morgenstern

We study the problem of designing truthful and fair mechanisms when allocating a mixture of divisible and indivisible goods. We first show that there does not exist an EFM (envy-free for mixed goods) and truthful mechanism in general. This…

Computer Science and Game Theory · Computer Science 2023-05-17 Zihao Li , Shengxin Liu , Xinhang Lu , Biaoshuai Tao

We consider distributed learning problem in games with an unknown cost-relevant parameter, and aim to find the Nash equilibrium while learning the true parameter. Inspired by the social learning literature, we propose a distributed…

Optimization and Control · Mathematics 2023-03-14 Shijie Huang , Jinlong Lei , Yiguang Hong

Recently, Press and Dyson have proposed a new class of probabilistic and conditional strategies for the two-player iterated Prisoner's Dilemma, so-called zero-determinant strategies. A player adopting zero-determinant strategies is able to…

Computer Science and Game Theory · Computer Science 2014-02-17 Liming Pan , Dong Hao , Zhihai Rong , Tao Zhou

The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk…

Theoretical Economics · Economics 2020-08-11 Christian Tarsney

In this work we consider an agent based model in order to study the wealth distribution problem where the interchange is determined with a symmetric zero sum game. Simultaneously, the agents update their way of play trying to learn the…

Physics and Society · Physics 2017-09-12 Juan Pablo Pinasco , Mauro Rodriguez Cartabia , Nicolas Saintier

Motivated by applications where impatience is pervasive and evaluation times are uncertain, we study a selection model where options may expire at an unknown point in time and evaluation times are stochastic. Initially, the decision-maker…

Optimization and Control · Mathematics 2026-02-05 Yihua Xu , Rohan Ghuge , Sebastian Perez-Salazar

We address the problem of fair division, or cake cutting, with the goal of finding truthful mechanisms. In the case of a general measure space ("cake") and non-atomic, additive individual preference measures - or utilities - we show that…

Computer Science and Game Theory · Computer Science 2010-10-27 Elchanan Mossel , Omer Tamuz

We study the fair allocation of undesirable indivisible items, or chores. While the case of desirable indivisible items (or goods) is extensively studied, with many results known for different notions of fairness, less is known about the…

Computer Science and Game Theory · Computer Science 2022-08-30 Umang Bhaskar , A. R. Sricharan , Rohit Vaish

We study the problem of allocating a set of indivisible goods among a set of agents in a fair and efficient manner. An allocation is said to be fair if it is envy-free up to one good (EF1), which means that each agent prefers its own bundle…

Computer Science and Game Theory · Computer Science 2018-05-14 Siddharth Barman , Sanath Kumar Krishnamurthy , Rohit Vaish

We study linear-quadratic games of incomplete information with Gaussian uncertainty, where each player's payoff depends on a privately observed type and a common state. The designer observes the state, elicits types, and sells action…

Computer Science and Game Theory · Computer Science 2025-11-04 Alessandro Bonatti , Munther A. Dahleh , Thibaut Horel

Reinforcement learning systems are often concerned with balancing exploration of untested actions against exploitation of actions that are known to be good. The benefit of exploration can be estimated using the classical notion of Value of…

Artificial Intelligence · Computer Science 2013-01-30 Richard Dearden , Nir Friedman , David Andre
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