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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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1.6%3.1%4.7%6.3% · Aug 199619922001200920172026
48 results for coarse-correlated equilibria

Paper develops efficient algorithms for learning rationalizable equilibria in multiplayer games.

problem Learning rationalizable behavior in multiplayer games under bandit feedback.
method New algorithms for finding rationalizable Coarse Correlated Equilibria and Correlated Equilibria with polynomial sample complexity.
result Achieved polynomial sample complexity for learning rationalizable equilibria, improving over existing exponential complexity.

Study explores optimal strategies in games with multiple players and mean-field interactions.

problem Optimal strategies in games with multiple players and mean-field interactions.
method Exploration of three different notions of optimality, including mean-field control solution, mean-field coarse correlated equilibria, and mean-field Nash equilibria.
result Approximation of cooperative and competitive equilibria in large NN-player games by mean-field control and mean-field equilibria.

New methods learn correlated equilibria in large games without structural assumptions.

problem Learning correlated equilibria in large, anonymous games with exponential player count.
method Developed Mean-Field correlated and coarse-correlated equilibria, and used classical algorithms to learn them efficiently.
result Efficiently learned correlated equilibria in all games without structural assumptions.

V-learning tackles multiagent reinforcement learning by reducing sample complexity.

problem Curse of multiagents in multiagent reinforcement learning.
method V-learning is a fully decentralized algorithm that learns Nash, correlated, and coarse correlated equilibria.
result V-learning achieves sample complexity that scales with the maximum number of actions per agent, not the joint action space.

Study efficient offline RL in Markov games with general models.

problem Learn approximate equilibria from offline data in Markov games.
method Use Bellman-consistent pessimism for interval estimation and optimize gap relaxation.
result First framework for sample-efficient offline learning in Markov games, handling all equilibria.

New approach tackles non-stationary multi-agent games with black-box methods.

problem Challenges in learning equilibria in non-stationary multi-agent systems.
method Versatile black-box approach applicable to various games, including general-sum, potential, and Markov games.
result Achieves optimal regret bounds for non-stationary games, with or without knowledge of total variation.

New MARL algorithms resolve the curse of multiagency with function approximation.

problem Challenges in Multi-Agent Reinforcement Learning (MARL) due to the curse of multiagency.
method V-Learning with Policy Replay and Decentralized Optimistic Policy Mirror Descent.
result First polynomial sample complexity results for learning approximate Coarse Correlated Equilibria (CCEs) of Markov Games under decentralized linear function approximation.

This paper tackles sample-efficient reinforcement learning for partially observable Markov games.

problem Learning in partially observable Markov games with incomplete information.
method A simple algorithm combining optimism and Maximum Likelihood Estimation (MLE) for self-play, and a variant of optimistic MLE for adversarial opponents.
result The proposed algorithms achieve approximate Nash, correlated, and coarse correlated equilibria in polynomial samples for weakly revealing POMGs.

Paper addresses inefficiency in converting EFGs to NFGs for learning.

problem Inefficiency in converting Extensive-Form Games to Normal-Form Games.
method Uses ΦΦ-Hedge algorithm and Online Mirror Descent (OMD) for polynomial-time learning of EFGs.
result Achieves O~(XAT)\widetilde{\mathcal{O}}(\sqrt{XAT}) EFCE-regret, matching information-theoretic lower bound.

This paper improves sample efficiency for learning equilibria in multi-player games.

problem Sample-efficient learning of equilibria in games with many players.
method Designs algorithms for learning CCE and CE with polynomial sample complexity in the number of players.
result First to show polynomial sample complexity for learning CCE and CE in multi-player games.

New algorithms for RL in Markov games with independent linear function approximation, breaking the curse of multiagents.

problem Tackles the challenge of learning Markov equilibria in large state space Markov games with multiple agents.
method Proposes independent linear Markov games and designs new algorithms for learning Markov coarse correlated equilibria and Markov correlated equilibria with polynomial sample complexity.
result Breaks the curse of multiagents by achieving sample complexity bounds that scale polynomially with each agent's function class complexity.

The notion of \emph{policy regret} in online learning is a well defined? performance measure for the common scenario of adaptive adversaries, which more traditional quantities such as external regret do not take into account. We revisit the notion of policy regret and first show that there are online learning settings …

2018-11-09abs ↗pdf ↗

Algorithm solves online binary classification and infinite games using ERM oracle.

problem Online learning and solving infinite games with computationally inefficient oracles.
method Proposes an algorithm relying solely on ERM oracle calls for online binary classification and nonparametric games.
result Achieves finite and sublinearly growing regret in various settings.

We introduce a quantitative approach to comparative statics that allows to bound the maximum effect of an exogenous parameter change on a system's equilibrium. The motivation for this approach is a well known paradox in multimarket Cournot competition, where a positive price shock on a monopoly market may actually redu…

2013-07-22abs ↗pdf ↗

Paper solves learning imperfect-information games with fewer episodes.

problem Learning imperfect-information extensive-form games from bandit feedback.
method Balanced Online Mirror Descent and Balanced Counterfactual Regret Minimization algorithms.
result Achieves near-optimal sample complexity for finding approximate Nash equilibria.

DREAM learns optimal strategies in imperfect games without needing a simulator.

problem Learning optimal strategies in imperfect-information games with multiple agents.
method DREAM is a deep reinforcement learning algorithm that converges to Nash Equilibria and coarse correlated equilibria.
result DREAM achieves state-of-the-art performance in benchmark games and is competitive with simulator-based algorithms.

We study the convergence of Nash equilibria in a game of optimal stopping. If the associated mean field game has a unique equilibrium, any sequence of nn-player equilibria converges to it as nn\to\infty. However, both the finite and infinite player versions of the game often admit multiple equilibria. We show that me…

2018-06-03abs ↗pdf ↗

The study examines different types of equilibria for stopping problems in one-dimensional diffusion processes.

problem Characterizing and comparing different types of equilibria for time-inconsistent stopping problems.
method Analyzes log sub-additive discount functions and one-dimensional diffusion processes to derive necessary and sufficient conditions for weak equilibria and other types of equilibria.
result Conditions for weak equilibria and their implications for other types of equilibria are provided.

Study network equilibria in saturated systems, revealing how small shocks can trigger major losses.

problem Understanding how small shocks can lead to major losses in financial networks and games.
method Derived explicit expressions for network equilibria, proved conditions for their uniqueness, and analyzed discontinuities.
result Bifurcation phenomenon in network equilibria, showing sensitivity to small shocks.

Study global geometry of dynamical systems with entire vector fields.

problem Understanding the global structure of equilibria and their basins.
method Step-by-step analysis of basins of centers, nodes, and foci; introduction of global elliptic sectors.
result Characterization of heteroclinic regions connecting equilibria.

New results on financial equilibria in markets with general semimartingales.

problem Existence and uniqueness of mean-variance equilibria in semimartingale markets.
method Analysis of dynamic mean-variance hedging and fixed-point problems.
result First results allowing for general semimartingales and both discrete and continuous time.

We prove a criterion for stability of relative equilibria in symmetric Hamiltonian systems at singular points of the momentum map. This generalizes a theorem of G.W. Patrick. The method of the proof is also useful in studying the bifurcation of relative equilibria.

1997-06-12abs ↗pdf ↗

This paper analyzes complex equilibria in a networked bivirus epidemic model.

problem Identify conditions for coexistence equilibria in a networked bivirus model.
method Employ Poincaré-Hopf Theorem with modifications and Morse inequalities.
result Establish properties on the local stability/instability of coexistence equilibria.

The paper proposes a method to learn continuous-action graphical games from perturbed equilibria.

problem Learning the exact structure of continuous-action graphical games from limited data.
method A 12\ell_{12}- block regularized method to recover the graphical game structure.
result The method recovers the exact structure of the graphical game under certain conditions.

New findings show pure strategy equilibria are more robust in a war of attrition game.

problem Analyzing a game of war of attrition under complete information.
method Examined the stability of equilibria in pure and mixed strategies under varying payoffs.
result Pure strategy equilibria are more robust to perturbations of the canonical model.

Optimal algorithm for two-player zero-sum games with linear parameterization.

problem Finding Nash Equilibrium in two-player zero-sum Markov games with linear transition.
method Nash-UCRL algorithm, Coarse Correlated Equilibrium, Optimism-in-Face-of-Uncertainty.
result Proves ildeO(dHT) ilde{O}(dH\sqrt{T}) regret bound, matching lower bound up to logarithmic factors.

In this paper the possibility of computing equilibrium in pure exchange and production economies by a homotopy method is investigated. The performance of the algorithm is tested on examples with known equilibria taken from the literature on general equilibrium models and numerical results are presented. In computing eq…

2011-10-24abs ↗pdf ↗

The study examines Nash equilibria in utility maximization games with multiplicative performance criteria.

problem Existence and uniqueness of Nash equilibria in multiplicative performance criteria games.
method General characterization of Nash equilibria for a large class of utility functions.
result Existence and uniqueness of Nash equilibria for arbitrary initial wealth vectors.

Study on symmetries and equilibria in Poisson manifolds, with applications to rigid body dynamics.

problem Characterizing conformal relative equilibria on Poisson manifolds.
method Introducing conformally Poisson actions and momentum maps, establishing algebraic criteria.
result Classification of nontrivial conformal relative equilibria in Lie algebras, with applications to rigid body dynamics.

We obtain a formula for the number of horizontal equilibria of a planar convex body KK with respect to a center of mass OO in terms of the winding number of the evolute of K\partial K with respect to OO. The formula extends to the case where OO lies on the evolute of K\partial K and a suitably modified version ho…

2019-09-12abs ↗pdf ↗

We present applications of the notion of isomorphic vector fields to the study of nonlinear stability of relative equilibria. Isomorphic vector fields were introduced by Hepworth [Theory Appl. Categ. 22 (2009), 542-587] in his study of vector fields on differentiable stacks. Here we argue in favor of the usefulness of …

2017-07-10abs ↗pdf ↗

Study optimal stopping times for multi-dimensional processes with non-exponential discounting.

problem Optimal stopping in multi-dimensional processes with non-exponential discounting.
method Probabilistic potential theory to establish existence of optimal equilibria.
result Existence of optimal equilibria for multi-dimensional stopping problems.

This work finds mixed equilibria in zero-sum games using interacting particle dynamics.

problem Finding mixed equilibrium points in continuous minmax games.
method A method based on entropic regularisation of two-layer zero-sum games with interacting particle dynamics.
result The sequence of empirical measures of the particle system satisfies a large deviation principle as the number of particles grows to infinity, implying convergence of the empirical measure and the Nikaidô-Isoda error.

Given a multifunction from XX to the kk-fold symmetric product Symk(X)Sym_k(X), we use the Dold-Thom Theorem to establish a homological selection Theorem. This is used to establish existence of Nash equilibria. Cost functions in problems concerning the existence of Nash Equilibria are traditionally multilinear in the mixe…

2011-11-03abs ↗pdf ↗

The paper solves portfolio optimization problems with risk constraints.

problem Maximizing utility while ensuring a certain wealth threshold with risk constraints.
method Derives Nash equilibria for two agents and characterizes them for more than two agents.
result Characterizes Nash equilibria for different cases of competition probabilities.