---
title: "Local-Effect Games"
authors:
  - "Kevin Leyton-Brown"
  - "Moshe Tennenholtz"
doi: ""
url: "https://ijcai.org/proceedings/2003/112"
pdf: "https://ijcai.org/proceedings/2003/0112.pdf"
venue: "Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence"
year: 2003
pages: "772-779"
track: ""
keywords:
---

# Local-Effect Games

Kevin Leyton-Brown, Moshe Tennenholtz

*Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence*, pages 772-779.

## Abstract

We present a new class of games, local-effect games (LEGs), which exploit structure in a different way from other compact game representations studied in AI. We show both theoretically and empirically that these games often (but not always) have pure-strategy Nash equilibria. Finding a potential function is a good technique for finding such equilibria. We give a complete characterization of which LEGs have potential functions and provide the functions in each case; we also show a general case where pure-strategy equilibria exist in the absence of potential functions. In experiments, we show that myopic best-response dynamics converge quickly to pure strategy equilibria in games not covered by our positive theoretical results.