# Distributed Inertial Best-Response Dynamics

arXiv: https://arxiv.org/abs/1605.00601 · HTML: https://mlsanity.com/paper/1605.00601/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 May 2016.

## Built on by (most cited first, 3 of 3)

- [Satisficing Paths and Independent Multi-Agent Reinforcement Learning in Stochastic Games](https://mlsanity.com/paper/2110.04638/) (2021)
- [Paths to Equilibrium in Games](https://mlsanity.com/paper/2403.18079/) (2024)
- [Grouped Satisficing Paths in Pure Strategy Games: a Topological Perspective](https://mlsanity.com/paper/2509.23157/) (2025)

## Abstract (arXiv)

The note considers the problem of computing pure Nash equilibrium (NE) strategies in distributed (i.e., network-based) settings. The paper studies a class of inertial best response dynamics based on the fictitious play (FP) algorithm. It is shown that inertial best response dynamics are robust to informational limitations common in distributed settings. Fully distributed variants of FP with inertia and joint strategy FP with inertia are developed and convergence is proven to the set of pure NE. The distributed algorithms rely on consensus methods. Results are validated using numerical simulations.