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We introduce a simple extensive-form algorithm for finding equilibria of two-player, zero-sum games. The algorithm is realization equivalent to a generalized form of Fictitious Play. We compare its performance to that of a similar…

Computer Science and Game Theory · Computer Science 2023-10-17 Tim P. Schulze

Hindsight rationality is an approach to playing general-sum games that prescribes no-regret learning dynamics for individual agents with respect to a set of deviations, and further describes jointly rational behavior among multiple agents…

Computer Science and Game Theory · Computer Science 2022-06-03 Dustin Morrill , Ryan D'Orazio , Marc Lanctot , James R. Wright , Michael Bowling , Amy R. Greenwald

An extensive literature in economics and social science addresses contests, in which players compete to outperform each other on some measurable criterion, often referred to as a player's score, or output. Players incur costs that are an…

Computer Science and Game Theory · Computer Science 2013-08-01 Leslie Ann Goldberg , Paul W. Goldberg , Piotr Krysta , Carmine Ventre

In this paper, we propose a framework for achieving long-term fair sequential decision making. By conducting both the hard and soft interventions, we propose to take path-specific effects on the time-lagged causal graph as a quantitative…

Machine Learning · Computer Science 2022-04-06 Yaowei Hu , Lu Zhang

In the game theory literature, there appears to be little research on equilibrium selection for normal-form games with an infinite strategy space and discontinuous utility functions. Moreover, many existing selection methods are not…

Computer Science and Game Theory · Computer Science 2018-09-24 Yuke Li , A. Stephen Morse

Discrete Choice Modelling serves as a robust framework for modelling human choice behaviour across various disciplines. Building a choice model is a semi structured research process that involves a combination of a priori assumptions,…

Econometrics · Economics 2025-06-09 Gabriel Nova , Sander van Cranenburgh , Stephane Hess

In mean-payoff games, the objective of the protagonist is to ensure that the limit average of an infinite sequence of numeric weights is nonnegative. In energy games, the objective is to ensure that the running sum of weights is always…

Computer Science and Game Theory · Computer Science 2012-09-17 Yaron Velner , Krishnendu Chatterjee , Laurent Doyen , Thomas A. Henzinger , Alexander Rabinovich , Jean-Francois Raskin

We study nondeterministic strategies in parity games with the aim of computing a most permissive winning strategy. Following earlier work, we measure permissiveness in terms of the average number/weight of transitions blocked by the…

Logic in Computer Science · Computer Science 2013-01-14 Patricia Bouyer , Nicolas Markey , Jörg Olschewski , Michael Ummels

Bayesian approaches developed to solve the optimal design of sequential experiments are mathematically elegant but computationally challenging. Recently, techniques using amortization have been proposed to make these Bayesian approaches…

Machine Learning · Computer Science 2022-06-20 Tom Blau , Edwin V. Bonilla , Iadine Chades , Amir Dezfouli

The accurate and personalized estimation of task difficulty provides many opportunities for optimizing user experience. However, user diversity makes such difficulty estimation hard, in that empirical measurements from some user sample do…

Human-Computer Interaction · Computer Science 2022-09-28 Jeppe Theiss Kristensen , Christian Guckelsberger , Paolo Burelli , Perttu Hämäläinen

Stackelberg games (SGs) constitute the most fundamental and acclaimed models of strategic interactions involving some form of commitment. Moreover, they form the basis of more elaborate models of this kind, such as, e.g., Bayesian…

Computer Science and Game Theory · Computer Science 2024-05-14 Francesco Bacchiocchi , Matteo Bollini , Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

Decision-making in large imperfect information games is difficult. Thanks to recent success in Poker, Counterfactual Regret Minimization (CFR) methods have been at the forefront of research in these games. However, most of the success in…

Artificial Intelligence · Computer Science 2019-05-28 Douglas Rebstock , Christopher Solinas , Michael Buro

Monte-Carlo counterfactual regret minimization (MCCFR) is the state-of-the-art algorithm for solving sequential games that are too large for full tree traversals. It works by using gradient estimates that can be computed via sampling.…

Computer Science and Game Theory · Computer Science 2020-02-21 Gabriele Farina , Christian Kroer , Tuomas Sandholm

We consider an application of the mathematical formalism of quantum mechanics (QM) outside physics, namely, to game theory. We present a simple game between macroscopic players, say Alice and Bob (or in a more complex form - Alice, Bob and…

Quantum Physics · Physics 2010-11-30 Andrei Khrennikov

The most important factors which contribute to the efficiency of game-theoretical algorithms are time and game complexity. In this study, we have offered an elegant method to deal with high complexity of game theoretic multi-objective…

Computer Science and Game Theory · Computer Science 2015-03-13 Mahsa Badami , Ali Hamzeh , Sattar Hashemi

Game theory is used by all behavioral sciences, but its development has long centered around tools for relatively simple games and toy systems, such as the economic interpretation of equilibrium outcomes. Our contribution, compositional…

Computer Science and Game Theory · Computer Science 2023-03-13 Seth Frey , Jules Hedges , Joshua Tan , Philipp Zahn

We study the problem of computing optimal correlated equilibria (CEs) in infinite-horizon multi-player stochastic games, where correlation signals are provided over time. In this setting, optimal CEs require history-dependent policies; this…

Computer Science and Game Theory · Computer Science 2025-06-10 Jiarui Gan , Rupak Majumdar

Tasks of different nature and difficulty levels are a part of people's lives. In this context, there is a scientific interest in the relationship between the difficulty of the task and the persistence need to accomplish it. Despite the…

Human-Computer Interaction · Computer Science 2024-04-25 Leonardo Ribeiro da Cunha , Leonardo Oliveira Mendes , Renio dos Santos Mendes

Heifetz, Meier, and Schipper (2013) introduced dynamic game with unawareness consisting of a partially ordered set of games in extensive form. Here, we study the normal form of dynamic games with unawareness. The generalized normal form…

Computer Science and Game Theory · Computer Science 2026-05-01 Burkhard C. Schipper

Graph games provide the foundation for modeling and synthesizing reactive processes. In the synthesis of stochastic reactive processes, the traditional model is perfect-information stochastic games, where some transitions of the game graph…

Logic in Computer Science · Computer Science 2016-04-22 Krishnendu Chatterjee , Laurent Doyen