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In this work we offer an $O(|V|^2 |E|\, W)$ pseudo-polynomial time deterministic algorithm for solving the Value Problem and Optimal Strategy Synthesis in Mean Payoff Games. This improves by a factor $\log(|V|\, W)$ the best previously…

Data Structures and Algorithms · Computer Science 2016-04-26 Carlo Comin , Romeo Rizzi

This paper studies parametric Markov decision processes (pMDPs), an extension to Markov decision processes (MDPs) where transitions probabilities are described by polynomials over a finite set of parameters. Fixing values for all parameters…

Logic in Computer Science · Computer Science 2019-04-03 Tobias Winkler , Sebastian Junges , Guillermo A. Pérez , Joost-Pieter Katoen

This paper presents a new lower bound for the discrete strategy improvement algorithm for solving parity games due to Voege and Jurdziski. First, we informally show which structures are difficult to solve for the algorithm. Second, we…

Computer Science and Game Theory · Computer Science 2009-01-20 Oliver Friedmann

We consider infinite duration alternating move games. These games were previously studied by Roth, Balcan, Kalai and Mansour. They presented an FPTAS for computing an approximated equilibrium, and conjectured that there is a polynomial…

Computer Science and Game Theory · Computer Science 2013-04-25 Yaron Velner

Under mean-variance-utility framework, we propose a new portfolio selection model, which allows wealth and time both have influences on risk aversion in the process of investment. We solved the model under a game theoretic framework and…

Portfolio Management · Quantitative Finance 2020-08-11 Ben-Zhang Yang , Xin-Jiang He , Song-Ping Zhu

This paper investigates value function approximation in the context of zero-sum Markov games, which can be viewed as a generalization of the Markov decision process (MDP) framework to the two-agent case. We generalize error bounds from MDPs…

Artificial Intelligence · Computer Science 2013-01-07 Michail Lagoudakis , Ron Parr

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

Optimization under uncertainty is a fundamental problem in learning and decision-making, particularly in multi-agent systems. Previously, Feldman, Kalai, and Tennenholtz [2010] demonstrated the ability to efficiently compete in repeated…

Computer Science and Game Theory · Computer Science 2026-01-29 Daniel Ablin , Alon Cohen

We study partial and budgeted versions of the well studied connected dominating set problem. In the partial connected dominating set problem, we are given an undirected graph G = (V,E) and an integer n', and the goal is to find a minimum…

Data Structures and Algorithms · Computer Science 2013-11-12 Samir Khuller , Manish Purohit , Kanthi Sarpatwar

Energy parity games are infinite two-player turn-based games played on weighted graphs. The objective of the game combines a (qualitative) parity condition with the (quantitative) requirement that the sum of the weights (i.e., the level of…

Logic in Computer Science · Computer Science 2012-04-04 Krishnendu Chatterjee , Laurent Doyen

We study policy optimization in an infinite horizon, $\gamma$-discounted constrained Markov decision process (CMDP). Our objective is to return a policy that achieves large expected reward with a small constraint violation. We consider the…

Machine Learning · Computer Science 2022-04-12 Arushi Jain , Sharan Vaswani , Reza Babanezhad , Csaba Szepesvari , Doina Precup

Mean-reverting portfolios with few assets, but high variance, are of great interest for investors in financial markets. Such portfolios are straightforwardly profitable because they include a small number of assets whose prices not only…

Optimization and Control · Mathematics 2021-04-19 Ahmad Mousavi , Jinglai Shen

This paper investigates a mean-field game (MFG) problem for mean-variance (MV) portfolio management, highlighting a new type of relative performance encoded by the peer-based risk aversion. Specifically, the risk aversion is formulated as a…

Mathematical Finance · Quantitative Finance 2026-05-26 Weilun Cheng , Zongxia Liang , Sheng Wang , Xiang Yu

Entropic risk (ERisk) is an established risk measure in finance, quantifying risk by an exponential re-weighting of rewards. We study ERisk for the first time in the context of turn-based stochastic games with the total reward objective.…

Computer Science and Game Theory · Computer Science 2023-07-14 Christel Baier , Krishnendu Chatterjee , Tobias Meggendorfer , Jakob Piribauer

This paper reframes approachability theory within the context of population games. Thus, whilst one player aims at driving her average payoff to a predefined set, her opponent is not malevolent but rather extracted randomly from a…

Optimization and Control · Mathematics 2014-07-16 Dario Bauso , Thomas W L Norman

Continuous-time empirical dynamic discrete choice games offer notable computational advantages over discrete-time models. This paper addresses remaining computational and econometric challenges to further improve both model solution and…

Econometrics · Economics 2025-11-11 Jason R. Blevins

In late May of 2014 I received an email from a colleague introducing to me a non-transitive game developed by Walter Penney. This paper explores this probability game from the perspective of a coin tossing game, and further discusses some…

Probability · Mathematics 2014-06-10 James Brofos

Mean-payoff games (MPGs) are infinite duration two-player zero-sum games played on weighted graphs. Under the hypothesis of perfect information, they admit memoryless optimal strategies for both players and can be solved in…

Logic in Computer Science · Computer Science 2015-04-14 Paul Hunter , Guillermo A. Pérez , Jean-François Raskin

We consider the problem of computing the value and an optimal strategy for minimizing the expected termination time in one-counter Markov decision processes. Since the value may be irrational and an optimal strategy may be rather…

Formal Languages and Automata Theory · Computer Science 2012-05-08 Tomáš Brázdil , Antonín Kučera , Petr Novotný , Dominik Wojtczak

We extend anytime constraints to the Markov game setting and the corresponding solution concept of an anytime-constrained equilibrium (ACE). Then, we present a comprehensive theory of anytime-constrained equilibria that includes (1) a…

Machine Learning · Computer Science 2025-03-05 Jeremy McMahan
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