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The celebrated Krusel-Smith growth model is an important example of a Mean Field Game with a common noise. The Mean Field Game is encoded in the master equation, a partial differential equation satisfied by the value of the game which…

Analysis of PDEs · Mathematics 2022-11-16 Yves Achdou , Jean-Michel Lasry , Pierre Louis Lions

Partially Observable Markov Decision Process (POMDP) is a framework applicable to many real world problems. In this work, we propose an approach to solve POMDPs with multimodal belief by relying on a policy that solves the fully observable…

Machine Learning · Computer Science 2022-07-26 András Attila Sulyok , Kristóf Karacs

This paper proposes Hodge Potential Choice (HPC), a new solution for abstract games with irreflexive dominance relations. This solution is formulated by involving geometric tools like differential forms and Hodge decomposition onto abstract…

Theoretical Economics · Economics 2024-07-17 Yihao Luo , Jinhui Pang , Weibin Han , Huafei Sun

Dynamic programming algorithms have been successfully applied to propositional stochastic planning problems by using compact representations, in particular algebraic decision diagrams, to capture domain dynamics and value functions. Work on…

Artificial Intelligence · Computer Science 2014-01-17 Saket Joshi , Roni Khardon

We study minority games in efficient regime. By incorporating the utility function and aggregating agents with similar strategies we develop an effective mesoscale notion of state of the game. Using this approach, the game can be…

Adaptation and Self-Organizing Systems · Physics 2011-12-06 Karol Wawrzyniak , Wojciech Wislicki

Stochastic optimal control and games have a wide range of applications, from finance and economics to social sciences, robotics, and energy management. Many real-world applications involve complex models that have driven the development of…

Optimization and Control · Mathematics 2024-03-12 Ruimeng Hu , Mathieu Laurière

Variable projection solves structured optimization problems by completely minimizing over a subset of the variables while iterating over the remaining variables. Over the last 30 years, the technique has been widely used, with empirical and…

Optimization and Control · Mathematics 2020-11-23 Tristan van Leeuwen , Aleksandr Aravkin

Typically, real-world stochastic processes are not easy to analyze. In this work we study the representation of any stochastic process as a memoryless innovation process triggering a dynamic system. We show that such a representation is…

Information Theory · Computer Science 2018-11-27 Amichai Painsky , Saharon Rosset , Meir Feder

In addressing the challenge of exponential scaling with the number of agents we adopt a cluster-based representation to approximately solve asymmetric games of very many players. A cluster groups together agents with a similar "strategic…

Computer Science and Game Theory · Computer Science 2012-06-18 Sevan G. Ficici , David C. Parkes , Avi Pfeffer

Coalition formation studies how to partition a set of agents into disjoint coalitions under consideration of their preferences. We study the classical objective of stability in a variant of additively separable hedonic games where agents…

Computer Science and Game Theory · Computer Science 2026-02-25 Fabian Frank , Matija Novaković , René Romen

This paper introduces a measure of uncertainty in the determination of the Shapley value, illustrates it with examples, and studies some of its properties. The introduced measure of uncertainty quantifies random variations in a player's…

General Mathematics · Mathematics 2007-09-03 Vladislav Kargin

This paper studies the complexity of computing a representation of a simple game as the intersection (union) of weighted majority games, as well as, the dimension or the codimension. We also present some examples with linear dimension and…

Computer Science and Game Theory · Computer Science 2016-02-16 Sascha Kurz , Xavier Molinero , Martin Olsen , Maria Serna

Computing and storing probabilities is a hard problem as soon as one has to deal with complex distributions over multiple random variables. The problem of efficient representation of probability distributions is central in term of…

Artificial Intelligence · Computer Science 2016-08-16 David Bellot , Pierre Bessiere

Online planning under uncertainty in partially observable domains is an essential capability in robotics and AI. The partially observable Markov decision process (POMDP) is a mathematically principled framework for addressing…

Robotics · Computer Science 2024-10-14 Da Kong , Vadim Indelman

This work is concerned with the propagation of uncertainty across coupled domain problems with high-dimensional random inputs. A stochastic model reduction approach based on low-rank separated representations is proposed for the partitioned…

Probability · Mathematics 2015-06-16 Mohammad Hadigol , Alireza Doostan , Hermann G. Matthies , Rainer Niekamp

In security games, the solution concept commonly used is that of a Stackelberg equilibrium where the defender gets to commit to a mixed strategy. The motivation for this is that the attacker can repeatedly observe the defender's actions and…

Computer Science and Game Theory · Computer Science 2016-10-17 Vincent Conitzer

This paper has a twofold scope. The first one is to clarify and put in evidence the isomorphic character of two theories developed in quite different fields: on one side, threshold logic, on the other side, simple games. One of the main…

Computer Science and Game Theory · Computer Science 2017-07-10 Josep Freixas , Marc Freixas , Sascha Kurz

Coalitional games are mathematical models suited to analyze scenarios where players can collaborate by forming coalitions in order to obtain higher worths than by acting in isolation. A fundamental problem for coalitional games is to single…

Computer Science and Game Theory · Computer Science 2013-07-19 Gianluigi Greco , Enrico Malizia , Luigi Palopoli , Francesco Scarcello

Calude et al. have recently shown that parity games can be solved in quasi-polynomial time, a landmark result that has led to a number of approaches with quasi-polynomial complexity. Jurdinski and Lasic have further improved the precise…

Data Structures and Algorithms · Computer Science 2022-11-18 Daniele Dell'Erba , Sven Schewe

For minimization problems without 2nd derivative information, methods that estimate Hessian matrices can be very effective. However, conventional techniques generate dense matrices that are prohibitive for large problems. Limited-memory…

Optimization and Control · Mathematics 2025-01-22 Johannes J. Brust