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How do incentive levels affect strategic behaviour? We address this with an experiment that separately identifies own- and opponent-incentive effects in two dominance-solvable games that differ in strategic complexity. Higher own incentives…

Theoretical Economics · Economics 2026-03-30 Teresa Esteban-Casanelles , Duarte Gonçalves

We present a novel model for capturing the behavior of an agent exhibiting sunk-cost bias in a stochastic environment. Agents exhibiting sunk-cost bias take into account the effort they have already spent on an endeavor when they evaluate…

Computer Science and Game Theory · Computer Science 2021-06-22 Jon Kleinberg , Sigal Oren , Manish Raghavan , Nadav Sklar

From skipped exercise classes to last-minute cancellation of dentist appointments, underutilization of reserved resources abounds. Likely reasons include uncertainty about the future, further exacerbated by present bias. In this paper, we…

Computer Science and Game Theory · Computer Science 2020-05-11 Hongyao Ma , Reshef Meir , David C. Parkes , Elena Wu-Yan

Inspired by real-time ad exchanges for online display advertising, we consider the problem of inferring a buyer's value distribution for a good when the buyer is repeatedly interacting with a seller through a posted-price mechanism. We…

Machine Learning · Computer Science 2013-11-28 Kareem Amin , Afshin Rostamizadeh , Umar Syed

Strategic classification studies the design of a classifier robust to the manipulation of input by strategic individuals. However, the existing literature does not consider the effect of competition among individuals as induced by the…

Computer Science and Game Theory · Computer Science 2022-02-23 Lydia T. Liu , Nikhil Garg , Christian Borgs

We consider the classical multi-armed bandit problem, but with strategic arms. In this context, each arm is characterized by a bounded support reward distribution and strategically aims to maximize its own utility by potentially retaining a…

Machine Learning · Computer Science 2025-01-28 Ahmed Ben Yahmed , Clément Calauzènes , Vianney Perchet

In a multi-battle contest, each time a player competes by investing some of her budgets or resources in a component battle to collect a value if winning the battle. There are multiple battles to fight, and the budgets get consumed over…

Computer Science and Game Theory · Computer Science 2016-02-15 Chu-Han Cheng , Po-An Chen , Wing-Kai Hon

This paper investigates the application of game-theoretic principles combined with advanced Kalman filtering techniques to enhance maritime target tracking systems. Specifically, the paper presents a two-player, imperfect information,…

Computer Science and Game Theory · Computer Science 2024-10-18 Daniel Leal , Ngoc Hung Nguyen , Alex Skvortsov , Sanjeev Arulampalam , Mahendra Piraveenan

Classic no-regret multi-armed bandit algorithms, including the Upper Confidence Bound (UCB), Hedge, and EXP3, are inherently unfair by design. Their unfairness stems from their objective of playing the most rewarding arm as frequently as…

Machine Learning · Computer Science 2024-05-14 Abhishek Sinha

Peer selection, the evaluation and selection of agents by their peers, is an important problem in the field of computational social choice; with applications to grading in massively online courses (MOOCs) and academic peer review. Current…

Computer Science and Game Theory · Computer Science 2026-05-26 Harper Lyon , Omer Lev , Nicholas Mattei

We study the optimal allocation of prizes in rank-order tournaments with loss averse agents. Prize sharing becomes increasingly optimal with loss aversion because more equitable prizes reduce the marginal psychological cost of anticipated…

Theoretical Economics · Economics 2024-11-05 Dmitry Ryvkin , Qin Wu

This paper investigates the dynamics of competition among organizations with unequal expertise. Multi-agent reinforcement learning has been used to simulate and understand the impact of various incentive schemes designed to offset such…

Computer Science and Game Theory · Computer Science 2022-01-06 Paramita Koley , Aurghya Maiti , Sourangshu Bhattacharya , Niloy Ganguly

Winners-take-all situations introduce an incentive for agents to diversify their behavior, since doing so will result in splitting an eventual price with fewer people. At the same time, when the payoff of a process depends on a parameter…

Computer Science and Game Theory · Computer Science 2019-06-11 Abel Molina

We investigate the most popular approaches to the problem of sports betting investment based on modern portfolio theory and the Kelly criterion. We define the problem setting, the formal investment strategies, and review their common…

Portfolio Management · Quantitative Finance 2021-07-20 Matej Uhrín , Gustav Šourek , Ondřej Hubáček , Filip Železný

We consider the coupled dynamics of the adaption of network structure and the evolution of strategies played by individuals occupying the network vertices. We propose a computational model in which each agent plays a $n$-round Prisoner's…

Physics and Society · Physics 2007-11-05 Feng Fu , Xiaojie Chen , Lianghuan Liu , Long Wang

Multi-armed Bandit motivates methods with provable upper bounds on regret and also the counterpart lower bounds have been extensively studied in this context. Recently, Multi-agent Multi-armed Bandit has gained significant traction in…

Machine Learning · Computer Science 2023-08-17 Mengfan Xu , Diego Klabjan

I study sequential contests where the efforts of earlier players may be disclosed to later players by nature or by design. The model has a range of applications, including rent seeking, R&D, oligopoly, public goods provision, and tragedy of…

Computer Science and Game Theory · Computer Science 2021-02-22 Toomas Hinnosaar

This article investigates the influence of luck and strategic considerations on performance of teams participating in the M6 investment challenge. We find that there is insufficient evidence to suggest that the extreme Sharpe ratios…

Portfolio Management · Quantitative Finance 2024-12-09 Filip Staněk

The problem of matching markets has been studied for a long time in the literature due to its wide range of applications. Finding a stable matching is a common equilibrium objective in this problem. Since market participants are usually…

Machine Learning · Computer Science 2023-07-21 Fang Kong , Shuai Li

We consider games played on finite graphs, whose goal is to obtain a trace belonging to a given set of winning traces. We focus on those states from which Player 1 cannot force a win. We explore and compare several criteria for establishing…

Computer Science and Game Theory · Computer Science 2008-11-12 Marco Faella