Skip to content

Similar papers

Preprint Sep 2026

Uniform-in-Time Boltzmann Mean-Field Limits for Anchored Binary Opinion Dynamics

We study a continuous-time opinion model in which agents interact in pairs and each agent has a fixed anchor. At each interaction epoch, both opinions are updated according to a possibly nonlinear rule with random inputs. Under suitable stability and moment assumptions, we establish uniform-in-time propagation of chaos...

Unknown authors · 0 citations
Preprint Aug 2026

Self-fictitious-play for Potential Monotone Ergodic Mean-field Games

We investigate long-time learning in ergodic, potential, monotone mean-field games (MFGs) via a self-fictitious-play (SFP) dynamics coupling an optimally controlled diffusion with a slowly evolving belief. At each time, the state follows the optimal feedback associated with the current belief, while the belief is updat...

Yupeng Bai, Mathieu Laurière, Zhen-Jie Ren et al. · 0 citations
Open access Jul 2026

Centrality-driven Sparse Optimal Control of Belief Formation in Social Networks

 This paper studies the problem of steering collective beliefs in social networks when only a small fraction of nodes can be directly influenced. We propose a sparse optimal control framework built on the Network Drift-Diffusion Model (NDDM). Two intervention mechanisms are considered: direct control and latent (indire...

Bo Wang · 0 citations
Preprint Aug 2026

Algorithmic Asymmetry in Zero-Sum Games: Unilateral Recovery of Fast Convergence Against a Slow Opponent

Learning dynamics in zero-sum games are typically analyzed under algorithmic symmetry: both agents use the same update rule, or methods from a common algorithmic family. This is at odds with the nature of zero-sum games; competing agents need not coordinate on algorithm selection. This paper studies algorithmic asymmet...

James P. Bailey, Soham Das · 0 citations
Preprint Jul 2026

Local Global Games and Network Common Learning

Network common learning is introduced, a network analogue of common learning, and it is shown that it is attained when neighboring agents'observations differ by many signals, as on the two-dimensional grid, but fails on networks with informational bottlenecks, such as the line.

Olga Rospuskova, Omer Tamuz, Jake Zhang · 0 citations
Preprint Aug 2026

Opinion Dynamics with Memory Loss and Communication Delays

A novel framework for modeling binary opinions of individuals connected through a weighted directed network, where edge weights quantify interpersonal influence is proposed, which allows individuals to update their biases using structured memory sets that capture limited and delayed information exchange.

Somya Singh, Sharayu Moharir, Neeraja Sahasrabudhe · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.