Cover Image

Machine-Learned Prediction Equilibrium for Dynamic Traffic Assignment

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Graf, Lukas, Harks, Tobias, Kollias, Kostas, Markl, Michael
Format:	Preprint
Published:	2021
Subjects:	Computer Science and Game Theory Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Stochastic Prediction Equilibrium for Dynamic Traffic Assignment
by: Graf, Lukas, et al.
Published: (2024)

Side-Constrained Dynamic Traffic Equilibria
by: Graf, Lukas, et al.
Published: (2022)

The Price of Anarchy for Instantaneous Dynamic Equilibria
by: Graf, Lukas, et al.
Published: (2020)

Are System Optimal Dynamic Flows Implementable by Tolls?
by: Graf, Lukas, et al.
Published: (2025)

Branch-and-Cut for Mixed-Integer Nash Equilibrium Problems
by: Duguet, Aloïs, et al.
Published: (2025)

An Equilibrium Dynamic Traffic Assignment Model with Linear Programming Formulation
by: Guseva, Victoria, et al.
Published: (2024)

Generalized Nash Equilibrium Problems with Mixed-Integer Variables
by: Harks, Tobias, et al.
Published: (2021)

Branch-and-Cut for Computing Approximate Equilibria of Mixed-Integer Generalized Nash Games
by: Duguet, Aloïs, et al.
Published: (2025)

Minimal Regret Walras Equilibria for Combinatorial Markets
by: Duguet, Aloïs, et al.
Published: (2025)

Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing
by: Bansak, Kirk, et al.
Published: (2020)

Last-Iterate Convergence of Adaptive Riemannian Gradient Descent for Equilibrium Computation
by: Cai, Yang, et al.
Published: (2023)

An Equilibrium Model for Schedule-Based Transit Networks with Hard Vehicle Capacities
by: Harks, Tobias, et al.
Published: (2024)

Carbon Pricing in Traffic Networks
by: Griesbach, Svenja M., et al.
Published: (2025)

Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach
by: Qiu, Shuang, et al.
Published: (2022)

An Exponentially Converging Particle Method for the Mixed Nash Equilibrium of Continuous Games
by: Wang, Guillaume, et al.
Published: (2022)

Synergistic Traffic Assignment
by: Bläsius, Thomas, et al.
Published: (2025)

Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games
by: Cai, Yang, et al.
Published: (2024)

PAPAL: A Provable PArticle-based Primal-Dual ALgorithm for Mixed Nash Equilibrium
by: Ding, Shihong, et al.
Published: (2023)

Deviation Between Team-Optimal Solution and Nash Equilibrium in Flow Assignment Problems
by: Xu, Gehui, et al.
Published: (2025)

Operator Splitting for Learning to Predict Equilibria in Convex Games
by: McKenzie, Daniel, et al.
Published: (2021)

MALADY: Multiclass Active Learning with Auction Dynamics on Graphs
by: Bhusal, Gokul, et al.
Published: (2024)

Enforcing Priority in Schedule-based User Equilibrium Transit Assignment
by: Feng, Liyang, et al.
Published: (2026)

Finite-Sample Guarantees for Learning Dynamics in Zero-Sum Polymatrix Games
by: Faizal, Fathima Zarin, et al.
Published: (2024)

Adaptive, Doubly Optimal No-Regret Learning in Strongly Monotone and Exp-Concave Games with Gradient Feedback
by: Jordan, Michael I., et al.
Published: (2023)

On the Convergence of Min-Max Langevin Dynamics and Algorithm
by: Cai, Yang, et al.
Published: (2024)

How Will the Presence of Autonomous Vehicles Affect the Equilibrium State of Traffic Networks?
by: Mehr, Negar, et al.
Published: (2019)

Data-Scarce Identification of Game Dynamics via Sum-of-Squares Optimization
by: Sakos, Iosif, et al.
Published: (2023)

Optimistic Online Learning in Symmetric Cone Games
by: Barakat, Anas, et al.
Published: (2025)

Reinforcement Learning for Finite Space Mean-Field Type Games
by: Shao, Kai, et al.
Published: (2024)

Exploiting Approximate Symmetry for Efficient Multi-Agent Reinforcement Learning
by: Yardim, Batuhan, et al.
Published: (2024)

Satisficing Paths and Independent Multi-Agent Reinforcement Learning in Stochastic Games
by: Yongacoglu, Bora, et al.
Published: (2021)

Faster Rates for No-Regret Learning in General Games via Cautious Optimism
by: Soleymani, Ashkan, et al.
Published: (2025)

Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms
by: Cai, Yang, et al.
Published: (2024)

Doubly Optimal No-Regret Online Learning in Strongly Monotone Games with Bandit Feedback
by: Ba, Wenjia, et al.
Published: (2021)

Unsupervised Solution Operator Learning for Mean-Field Games via Sampling-Invariant Parametrizations
by: Huang, Han, et al.
Published: (2024)

On Separation Between Best-Iterate, Random-Iterate, and Last-Iterate Convergence of Learning in Games
by: Cai, Yang, et al.
Published: (2025)

A Deep Learning Method for Optimal Investment Under Relative Performance Criteria Among Heterogeneous Agents
by: Laurière, Mathieu, et al.
Published: (2024)

Dynamic traffic assignment in a corridor network: Optimum versus Equilibrium
by: Fu, Haoran, et al.
Published: (2021)

Generalized Quantal Response Equilibrium: Existence and Efficient Learning
by: Shukla, Apurv, et al.
Published: (2025)

Near Optimal Convergence to Coarse Correlated Equilibrium in General-Sum Markov Games
by: Yorulmaz, Asrin Efe, et al.
Published: (2025)