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Related papers: Nash Equilibria in Optimal Reinsurance Bargaining

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If a game has a unique Nash equilibrium, then this equilibrium is arguably the solution of the game from the refinement's literature point of view. However, it might be that for almost all initial conditions, all strategies in the support…

Computer Science and Game Theory · Computer Science 2012-11-26 Yannick Viossat

Under the assumption of complete rationality, Nash equilibrium is the only reasonable strategy (set) of the finitely repeated prisoner's dilemma. In fact, some strategies only slightly deviate from the so-called rationality, and the…

Computer Science and Game Theory · Computer Science 2014-01-09 Xuegong Deng

Optimal reinsurance when Value at Risk and expected surplus is balanced through their ratio is studied, and it is demonstrated how results for risk-adjusted surplus can be utilized. Simplifications for large portfolios are derived, and this…

Applications · Statistics 2019-12-10 Erik Bølviken , Yinzhi Wang

We study selection acting on phenotype in a collection of agents playing local games lacking Nash equilibria. After each cycle one of the agents losing most games is replaced by a new agent with new random strategy and game partner. The…

Statistical Mechanics · Physics 2007-05-23 Daniel Eriksson , Henrik Jeldtoft Jensen

Most work in mechanism design assumes that buyers are risk neutral; some considers risk aversion arising due to a non-linear utility for money. Yet behavioral studies have established that real agents exhibit risk attitudes which cannot be…

Computer Science and Game Theory · Computer Science 2018-03-13 Shuchi Chawla , Kira Goldner , J. Benjamin Miller , Emmanouil Pountourakis

In this paper a consensus has been constructed in a social network which is modeled by a stochastic differential game played by agents of that network. Each agent independently minimizes a cost function which represents their motives. A…

Statistics Theory · Mathematics 2021-07-13 Paramahansa Pramanik

To achieve an optimal outcome in many situations, agents need to choose distinct actions from one another. This is the case notably in many resource allocation problems, where a single resource can only be used by one agent at a time. How…

Computer Science and Game Theory · Computer Science 2014-02-05 Ludek Cigler , Boi Faltings

Artificially intelligent agents are increasingly being integrated into human decision-making: from large language model (LLM) assistants to autonomous vehicles. These systems often optimize their individual objective, leading to conflicts,…

Machine Learning · Computer Science 2025-02-07 Juan Agustin Duque , Milad Aghajohari , Tim Cooijmans , Razvan Ciuca , Tianyu Zhang , Gauthier Gidel , Aaron Courville

The introduction of aggregator structures has proven effective in bringing fairness to energy resource allocation by negotiating for more resources and economic surplus on behalf of users. This paper extends the fair energy resource…

Computer Science and Game Theory · Computer Science 2024-10-16 Jiayi Li , Matt Motoki , Baosen Zhang

The relative arbitrage portfolio outperforms a benchmark portfolio over a given time-horizon with probability one. With market price of risk processes depending on the market portfolio and investors, this paper analyzes the multi-agent…

Mathematical Finance · Quantitative Finance 2026-04-23 Tomoyuki Ichiba , Nicole Tianjiao Yang

In this paper, we study a class of discrete-time mean-field games under the infinite-horizon risk-sensitive discounted-cost optimality criterion. Risk-sensitivity is introduced for each agent (player) via an exponential utility function. In…

Optimization and Control · Mathematics 2018-10-08 Naci Saldi , Tamer Basar , Maxim Raginsky

The standard risk minimization paradigm of machine learning is brittle when operating in environments whose test distributions are different from the training distribution due to spurious correlations. Training on data from many…

Machine Learning · Computer Science 2020-03-20 Kartik Ahuja , Karthikeyan Shanmugam , Kush R. Varshney , Amit Dhurandhar

We study optimal execution in markets with transient price impact in a competitive setting with $N$ traders. Motivated by prior negative results on the existence of pure Nash equilibria, we consider randomized strategies for the traders and…

Trading and Market Microstructure · Quantitative Finance 2026-05-19 Steven Campbell , Marcel Nutz

We study a common-pool resource game where the resource experiences failure with a probability that grows with the aggregate investment in the resource. To capture decision making under such uncertainty, we model each player's risk…

Computer Science and Game Theory · Computer Science 2016-07-04 Ashish R. Hota , Siddharth Garg , Shreyas Sundaram

In socio-technical multi-agent systems, deception exploits privileged information to induce false beliefs in "victims," keeping them oblivious and leading to outcomes detrimental to them or advantageous to the deceiver. We consider…

Systems and Control · Electrical Eng. & Systems 2025-07-08 Michael Tang , Umar Javed , Xudong Chen , Miroslav Krstic , Jorge I. Poveda

We consider the problem of learning Nash equilibrial policies for two-player risk-sensitive collision-avoiding interactions. Solving the Hamilton-Jacobi-Isaacs equations of such general-sum differential games in real time is an open…

Robotics · Computer Science 2025-03-21 Lei Zhang , Siddharth Das , Tanner Merry , Wenlong Zhang , Yi Ren

Many multiagent systems rely on collective decision-making among self-interested agents, which raises deep questions about coalition formation and stability. We study social choice with endogenous, outcome-contingent transfers, where agents…

Theoretical Economics · Economics 2026-01-23 Joshua Kavner

We study risk-sharing economies where heterogenous agents trade subject to quadratic transaction costs. The corresponding equilibrium asset prices and trading strategies are characterised by a system of nonlinear, fully-coupled…

Portfolio Management · Quantitative Finance 2020-10-01 Martin Herdegen , Johannes Muhle-Karbe , Dylan Possamaï

The control of large-scale, multi-agent systems often entails distributing decision-making across the system components. However, with advances in communication and computation technologies, we can consider new collaborative decision-making…

Computer Science and Game Theory · Computer Science 2024-07-04 Bryce L. Ferguson , Dario Paccagnan , Bary S. R. Pradelski , Jason R. Marden

We propose a new variant of the strategic classification problem: a principal reveals a classifier, and $n$ agents report their (possibly manipulated) features to be classified. Motivated by real-world applications, our model crucially…

Computer Science and Game Theory · Computer Science 2025-02-28 Safwan Hossain , Evi Micha , Yiling Chen , Ariel Procaccia
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