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We study sequential decision-making when the agent's internal model class is misspecified. Within the infinite-horizon Berk-Nash framework, stable behavior arises as a fixed point: the agent acts optimally relative to a subjective model,…

Computer Science and Game Theory · Computer Science 2026-03-17 Quanyan Zhu , Zhengye Han

Empirically, many strategic settings are characterized by stable outcomes in which players' decisions are publicly observed, yet no player takes the opportunity to deviate. To analyze such situations in the presence of incomplete…

Econometrics · Economics 2024-04-12 Paul S. Koh

It is common to assume that agents will adopt Nash equilibrium strategies; however, experimental studies have demonstrated that Nash equilibrium is often a poor description of human players' behavior in unrepeated normal-form games. In this…

Computer Science and Game Theory · Computer Science 2017-10-17 James R. Wright , Kevin Leyton-Brown

Game theory provides a well-established framework for the analysis of concurrent and multi-agent systems. The basic idea is that concurrent processes (agents) can be understood as corresponding to players in a game; plays represent the…

Logic in Computer Science · Computer Science 2023-06-22 Julian Gutierrez , Paul Harrenstein , Giuseppe Perelli , Michael Wooldridge

A quantum financial approach to finite games of strategy is addressed, with an extension of Nash's theorem to the quantum financial setting, allowing for an entanglement of games of strategy with two-period financial allocation problems…

General Finance · Quantitative Finance 2012-02-10 Carlos Pedro Gonçalves

Auctions are modeled as Bayesian games with continuous type and action spaces. Determining equilibria in auction games is computationally hard in general and no exact solution theory is known. We introduce an algorithmic framework in which…

Computer Science and Game Theory · Computer Science 2023-05-10 Martin Bichler , Maximilian Fichtl , Matthias Oberlechner

We address the problem of assessing the robustness of the equilibria in uncertain, multi-agent games. Specifically, we focus on generalized Nash equilibrium problems in aggregative form subject to linear coupling constraints affected by…

Optimization and Control · Mathematics 2020-05-20 Filippo Fabiani , Kostas Margellos , Paul J. Goulart

Nash equilibria provide a principled framework for modeling interactions in multi-agent decision-making and control. However, many equilibrium-seeking methods implicitly assume that each agent has access to the other agents' objectives and…

Computer Science and Game Theory · Computer Science 2026-03-19 Mahdis Rabbani , Navid Mojahed , Shima Nazari

Consider a strongly monotone game where the players' utility functions include a reward function and a linear term for each dimension, with coefficients that are controlled by the manager. Gradient play converges to a unique Nash…

Multiagent Systems · Computer Science 2026-02-25 Siddharth Chandak , Ilai Bistritz , Nicholas Bambos

We consider a market impact game for $n$ risk-averse agents that are competing in a market model with linear transient price impact and additional transaction costs. For both finite and infinite time horizons, the agents aim to minimize a…

Trading and Market Microstructure · Quantitative Finance 2020-10-30 Xiangge Luo , Alexander Schied

We consider shared workspace scenarios with humans and robots acting to achieve independent goals, termed as parallel play. We model these as general-sum games and construct a framework that utilizes the Nash equilibrium solution concept to…

Artificial Intelligence · Computer Science 2020-06-11 Shray Bansal , Jin Xu , Ayanna Howard , Charles Isbell

We propose a tractable unified framework to study the evolution and interaction of model-misspecification concerns and complexity aversion in repeated decision problems. This aims to capture environments where decision makers worry that…

Theoretical Economics · Economics 2026-02-18 Drew Fudenberg , Florian Mudekereza

Modeling social interactions is a challenging task that requires flexible frameworks. For instance, dissimulation and externalities are relevant features influencing such systems -- elements that are often neglected in popular models. This…

Optimization and Control · Mathematics 2022-12-21 Yuri Saporito , Max O. Souza , Yuri Thamsten

Machine learning models are vulnerable to adversarial examples: minor perturbations to input samples intended to deliberately cause misclassification. While an obvious security threat, adversarial examples yield as well insights about the…

Cryptography and Security · Computer Science 2019-11-19 Kathrin Grosse , David Pfaff , Michael Thomas Smith , Michael Backes

Accurately modeling and verifying the correct operation of systems interacting in dynamic environments is challenging. By leveraging parametric uncertainty within the model description, one can relax the requirement to describe exactly the…

Optimization and Control · Mathematics 2016-04-05 Patrick Holmes , Shreyas Kousik , Shankar Mohan , Ram Vasudevan

We consider the problem of a game theorist analyzing a game that uses cryptographic protocols. Ideally, a theorist abstracts protocols as ideal, implementation-independent primitives, letting conclusions in the "ideal world" carry over to…

Computer Science and Game Theory · Computer Science 2025-06-30 Alexandros Psomas , Athina Terzoglou , Yu Wei , Vassilis Zikas

In this paper, a Nash-type fictitious game framework is introduced to handle a time-inconsistent linear-quadratic optimal control. The Nash-type game in this framework is called fictitious as it is between the decision maker (called real…

Optimization and Control · Mathematics 2021-10-04 Yuan-Hua Ni , Binbin Si , Xinzhen Zhang

We introduce an extended mathematical programming framework for specifying equilibrium problems and their variational representations, such as generalized Nash equilibrium, multiple optimization problems with equilibrium constraints, and…

Optimization and Control · Mathematics 2018-06-07 Youngdae Kim , Michael C. Ferris

In this study, we present models where participants strategically select their risk levels and earn corresponding rewards, mirroring real-world competition across various sectors. Our analysis starts with a normal form game involving two…

Computational Finance · Quantitative Finance 2023-05-31 Louis Abraham

Standard simulations of the Iterated Prisoners Dilemma (IPD) operate in deterministic, noise-free environments, producing strategies that may be theoretically optimal but fragile when confronted with real-world uncertainty. This paper…

Neural and Evolutionary Computing · Computer Science 2026-01-07 Oguzhan Yildirim