English
Related papers

Related papers: Compromise, Don't Optimize: Generalizing Perfect B…

200 papers

An unconventional approach for optimal stopping under model ambiguity is introduced. Besides ambiguity itself, we take into account how ambiguity-averse an agent is. This inclusion of ambiguity attitude, via an $\alpha$-maxmin nonlinear…

Mathematical Finance · Quantitative Finance 2021-07-15 Yu-Jui Huang , Xiang Yu

A Bayesian game is a game of incomplete information in which the rules of the game are not fully known to all players. We consider the Bayesian game of Battle of Sexes that has several Bayesian Nash equilibria and investigate its outcome…

Quantum Physics · Physics 2014-11-19 Azhar Iqbal , James M. Chappell , Qiang Li , Charles E. M. Pearce , Derek Abbott

In dynamic games with asymmetric information structure, the widely used concept of equilibrium is perfect Bayesian equilibrium (PBE). This is expressed as a strategy and belief pair that simultaneously satisfy sequential rationality and…

Computer Science and Game Theory · Computer Science 2016-09-15 Abhinav Sinha , Achilleas Anastasopoulos

A new concept of an equilibrium in games is introduced that solves an open question posed by A. Neyman.

Economics · Quantitative Finance 2019-01-08 R. Simon , S. Spiez , H. Torunczyk

We introduce a class of extensive form games where players might not be able to foresee the possible consequences of their decisions and form a model of their opponents which they exploit to achieve a more profitable outcome. We improve…

Artificial Intelligence · Computer Science 2016-05-31 Paolo Turrini

This paper investigates the equilibrium portfolio selection for smooth ambiguity preferences in a continuous-time market. The investor is uncertain about the risky asset's drift term and updates the subjective belief according to the…

Optimization and Control · Mathematics 2023-02-17 Guohui Guan , Zongxia Liang , Jianming Xia

Bayesian optimization is a coherent, ubiquitous approach to decision-making under uncertainty, with applications including multi-arm bandits, active learning, and black-box optimization. Bayesian optimization selects decisions (i.e.…

Machine Learning · Computer Science 2023-12-13 Samuel Stanton , Wesley Maddox , Andrew Gordon Wilson

Modeling the interaction between traffic agents is a key issue in designing safe and non-conservative maneuvers in autonomous driving. This problem can be challenging when multi-modality and behavioral uncertainties are engaged. Existing…

Robotics · Computer Science 2024-09-24 Zhenmin Huang , Tong Li , Shaojie Shen , Jun Ma

We study equilibrium concepts in non-cooperative games under uncertainty where both beliefs and mixed strategies are represented by non-additive measures (capacities). In contrast to the classical Nash framework based on additive…

Computer Science and Game Theory · Computer Science 2026-03-06 Taras Radul

We introduce a notion of subgames for stochastic timing games and the related notion of subgame-perfect equilibrium in possibly mixed strategies. While a good notion of subgame-perfect equilibrium for continuous-time games is not available…

Optimization and Control · Mathematics 2018-05-23 Frank Riedel , Jan-Henrik Steg

We propose a general definition of perfect equilibrium which is applicable to a wide class of games. A key feature is the concept of completely mixed nets of strategies, based on a more detailed notion of carrier of a strategy. Under…

Theoretical Economics · Economics 2025-11-21 János Flesch , Christopher Kops , Dries Vermeulen , Anna Zseleva

We consider the problem of how decision making can be fair when the underlying probabilistic model of the world is not known with certainty. We argue that recent notions of fairness in machine learning need to explicitly incorporate…

Machine Learning · Computer Science 2018-11-06 Christos Dimitrakakis , Yang Liu , David Parkes , Goran Radanovic

In this paper, we consider a distributed Bayesian Nash equilibrium (BNE) seeking problem in incomplete-information aggregative games, which is a generalization of Bayesian games and deterministic aggregative games. We handle the aggregation…

Optimization and Control · Mathematics 2023-09-19 Hanzheng Zhang , Guanpu Chen , Huashu Qin

This paper introduces risk-revising players to a class of games with incomplete information. These players enter the game with ex ante risk preferences represented by coherent risk measures and develop time-consistent interim revisions of…

Optimization and Control · Mathematics 2026-03-23 Shutian Liu

We consider finite-horizon and infinite-horizon versions of a dynamic game with $N$ selfish players who observe their types privately and take actions that are publicly observed. Players' types evolve as conditionally independent Markov…

Optimization and Control · Mathematics 2018-03-20 Deepanshu Vasal , Abhinav Sinha , Achilleas Anastasopoulos

This work addresses the classic machine learning problem of online prediction with expert advice. We consider the finite-horizon version of this zero-sum, two-person game. Using verification arguments from optimal control theory, we view…

Machine Learning · Computer Science 2020-06-30 Vladimir A. Kobzar , Robert V. Kohn , Zhilei Wang

The conditional commitment abilities of mutually transparent computer agents have been studied in previous work on commitment games and program equilibrium. This literature has shown how these abilities can help resolve Prisoner's Dilemmas…

Computer Science and Game Theory · Computer Science 2022-12-06 Anthony DiGiovanni , Jesse Clifton

We propose an extensive-form solution concept, with players that neglect information from hypothetical events, but make inferences from observed events. Our concept modifies cursed equilibrium (Eyster and Rabin, 2005), and allows that…

Theoretical Economics · Economics 2025-07-29 Shani Cohen , Shengwu Li

We consider a setting in which a principal gets to choose which game from some given set is played by a group of agents. The principal would like to choose a game that favors one of the players, the social preferences of the players, or the…

Computer Science and Game Theory · Computer Science 2025-11-27 Caspar Oesterheld , Vincent Conitzer

We introduce a "high probability" framework for repeated games with incomplete information. In our non-equilibrium setting, players aim to guarantee a certain payoff with high probability, rather than in expected value. We provide a high…

Computer Science and Game Theory · Computer Science 2015-09-30 Payam Delgosha , Amin Gohari , Mohammad Akbarpour