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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.

168,657 papers · 148 categories

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19395877 · Jun 202019922001200920172026
48 results for Markov equilibria

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.

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.

The existence of stationary Markov perfect equilibria in stochastic games is shown under a general condition called "(decomposable) coarser transition kernels". This result covers various earlier existence results on correlated equilibria, noisy stochastic games, stochastic games with finite actions and state-independe…

2013-11-07abs ↗pdf ↗

Algorithm converges to Nash equilibria in competitive games.

problem Finding Nash equilibria in decentralized, competitive Markov games.
method Decentralized Optimistic Gradient Descent/Ascent with a critic.
result Converges to the set of Nash equilibria under self-play.

Algorithm minimizes regret and converges to equilibria in Markov games.

problem Regret minimization and convergence to equilibria in general-sum Markov games under adversarial opponents.
method Decentralized algorithm that uses policy optimization and controls path length to achieve sublinear regret.
result Sublinear regret guarantees for convergence to correlated equilibrium in Markov games.

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 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.

This work tackles robust RL in multi-agent settings, improving sample efficiency.

problem Overcoming environmental uncertainties in multi-agent reinforcement learning.
method Proposes DRNVI, a sample-efficient algorithm for learning robust equilibria in RMGs.
result Establishes near-optimal sample complexity for solving RMGs.

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.

Algorithm finds Nash equilibria in complex games with function approximation.

problem Learning Nash equilibria in two-player zero-sum Markov Games with nonlinear function approximation.
method Online learning algorithm using upper and lower confidence bounds derived from optimism in the face of uncertainty.
result Achieves O(T)O(\sqrt{T}) regret with polynomial complexity, under mild assumptions.

Pessimistic model-based algorithm finds Nash equilibria in zero-sum Markov games from offline data.

problem Learning Nash equilibria in two-player zero-sum Markov games from limited data.
method Pessimistic model-based algorithm with Bernstein-style lower confidence bounds (VI-LCB-Game).
result Proves sample complexity no larger than CclippedS(A+B)(1γ)3ε2\frac{C_{\mathsf{clipped}}^\star S(A+B)}{(1-γ)^3 \varepsilon^2}, achieving minimax optimality.

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.

Method locates equilibria on unknown Riemannian manifolds using iterative sampling and parallel transport.

problem Locating equilibria on unknown Riemannian manifolds defined by point-clouds.
method Iterative sampling, parallel transport, and generalized isoclines.
result Algorithm reliably locates equilibria of dynamical systems on unknown manifolds.

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.

There is an increasing demand for computing the relevant structures, equilibria and long-timescale kinetics of biomolecular processes, such as protein-drug binding, from high-throughput molecular dynamics simulations. Current methods employ transformation of simulated coordinates into structural features, dimension red…

2017-10-16abs ↗pdf ↗

In this paper, we investigate the geometry of a general class of gradient flows with multiple local maxima. we decompose the underlying space into disjoint regions of attraction and establish the adjacency criterion. The criterion states a necessary and sufficient condition for two regions of attraction of stable equil…

2014-12-21abs ↗pdf ↗

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.

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 ↗

Almost all of the work in graphical models for game theory has mirrored previous work in probabilistic graphical models. Our work considers the opposite direction: Taking advantage of recent advances in equilibrium computation for probabilistic inference. We present formulations of inference problems in Markov random f…

2016-04-10abs ↗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.

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 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.

Imitation learning algorithms can be used to learn a policy from expert demonstrations without access to a reward signal. However, most existing approaches are not applicable in multi-agent settings due to the existence of multiple (Nash) equilibria and non-stationary environments. We propose a new framework for multi-…

2018-07-26abs ↗pdf ↗

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.

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.

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 ↗

New RL algorithms find SNE in Markov games with myopic followers.

problem Finding SNE in Markov games with myopic followers.
method Optimistic and pessimistic variants of least-squares value iteration, incorporating function approximation.
result First provably efficient RL algorithms for SNEs in general-sum Markov games with myopic followers.

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 ↗

We undertake a fundamental study of network equilibria modeled as solutions of fixed point equations for monotone linear functions with saturation nonlinearities. The considered model extends one originally proposed to study systemic risk in networks of financial institutions interconnected by mutual obligations and is…

2019-12-10abs ↗pdf ↗

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 ↗