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We develop the thermodynamics of non-Markovian generalized Langevin equations by embedding them in a high-dimensional Markovian representation involving auxiliary degrees of freedom. If the memory is linear and satisfies detailed balance…

Statistical Mechanics · Physics 2026-04-29 Andreas Dechant , Kiyoshi Kanazawa

We motivate and propose a new model for non-cooperative Markov game which considers the interactions of risk-aware players. This model characterizes the time-consistent dynamic "risk" from both stochastic state transitions (inherent to the…

Computer Science and Game Theory · Computer Science 2019-11-22 Wenjie Huang , Pham Viet Hai , William B. Haskell

We present embedding procedures for the non-Markovian stochastic Schr\"{o}dinger equations, arising from studies of quantum systems coupled with bath environments. By introducing auxiliary wave functions, it is demonstrated that the…

Computational Physics · Physics 2020-05-04 Xiantao Li

We present a systematic investigation of the quantum games, constructed using a novel repeated game protocol, when played repeatedly ad infinitum. We focus on establishing that such repeated games -- by virtue of inherent quantum-mechanical…

Quantum Physics · Physics 2024-02-27 Archan Mukhopadhyay , Saikat Sur , Tanay Saha , Shubhadeep Sadhukhan , Sagar Chakraborty

We study the interaction between strategy, heterogeneity and growth in a two-agent model of capital accumulation. Preferences are represented by recursive utility functions with decreasing marginal impatience. The stationary equilibria of…

Optimization and Control · Mathematics 2016-08-26 Luis Alcala , Fernando Tohme , Carlos Dabus

We study uncoordinated matching markets with additional local constraints that capture, e.g., restricted information, visibility, or externalities in markets. Each agent is a node in a fixed matching network and strives to be matched to…

Computer Science and Game Theory · Computer Science 2014-09-16 Martin Hoefer , Lisa Wagner

This paper studies value iteration for infinite horizon contracting Markov decision processes under convexity assumptions and when the state space is uncountable. The original value iteration is replaced with a more tractable form and the…

Optimization and Control · Mathematics 2018-02-21 Jeremy Yee

The article introduces a notion of a stochastic game with failure states and proposes two logical systems with modality "coalition has a strategy to transition to a non-failure state with a given probability while achieving a given goal."…

Artificial Intelligence · Computer Science 2019-10-11 Pavel Naumov , Kevin Ros

A Markovian modulation captures the trend in the market and influences the market coefficients accordingly. The different scenarios presented by the market are modeled as the distinct states of a discrete-time Markov chain. In our paper, we…

Optimization and Control · Mathematics 2022-02-09 Bernardo D'Auria , José A. Salmerón

Stochastic differential games are considered in a non-Markovian setting. Typically, in stochastic differential games the modulating process of the diffusion equation describing the state flow is taken to be Markovian. Then Nash equilibria…

Information Theory · Computer Science 2007-07-13 Erhan Bayraktar , H. Vincent Poor

Aiming to provide a new class of game dynamics with good long-term rationality properties, we derive a second-order inertial system that builds on the widely studied "heavy ball with friction" optimization method. By exploiting a well-known…

Optimization and Control · Mathematics 2015-03-03 Rida Laraki , Panayotis Mertikopoulos

Cooperative bargaining games are widely used to model resource allocation and conflict resolution. Traditional solutions assume the mediator can access agents utility function values and gradients. However, there is an increasing number of…

Computer Science and Game Theory · Computer Science 2025-10-20 Kushagra Gupta , Surya Murthy , Mustafa O. Karabag , Ufuk Topcu , David Fridovich-Keil

Traditionally social sciences are interested in structuring people in multiple groups based on their individual preferences. This pa- per suggests an approach to this problem in the framework of a non- cooperative game theory. Definition of…

Optimization and Control · Mathematics 2017-05-02 Dmitry Levando

Optimal policies in standard MDPs can be obtained using either value iteration or policy iteration. However, in the case of zero-sum Markov games, there is no efficient policy iteration algorithm; e.g., it has been shown that one has to…

Machine Learning · Computer Science 2023-10-31 Anna Winnicki , R. Srikant

The paper introduces a modified version of the classical Coupon Collector's Problem entailing exchanges and cooperation between multiple players. Results of the development show that, within a proper Markov framework, the complexity of the…

Discrete Mathematics · Computer Science 2009-12-15 R. Rovatti , C. Passerini , G. Mazzini

In many stochastic games stemming from financial models, the environment evolves with latent factors and there may be common noise across agents' states. Two classic examples are: (i) multi-agent trading on electronic exchanges, and (ii)…

Optimization and Control · Mathematics 2019-07-24 Dena Firoozi , Peter E. Caines , Sebastian Jaimungal

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

Stochastic games are an important class of problems that generalize Markov decision processes to game theoretic scenarios. We consider finite state two-player zero-sum stochastic games over an infinite time horizon with discounted rewards.…

Optimization and Control · Mathematics 2008-06-17 Parikshit Shah , Pablo A. Parrilo

We present a computational model to reconstruct trees of ancestors for animals with sexual reproduction. Through a recursive algorithm combined with a random number generator, it is possible to reproduce the number of ancestors for each…

Populations and Evolution · Quantitative Biology 2019-08-19 C. Jarne , M. Caruso

Multi-agent reinforcement learning has been successfully applied to fully-cooperative and fully-competitive environments, but little is currently known about mixed cooperative/competitive environments. In this paper, we focus on a…

Machine Learning · Computer Science 2021-10-22 Roy Fox , Stephen McAleer , Will Overman , Ioannis Panageas
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