Christian Robert Shelton 

Title:  Compact Structured Game Representations

Abstract:

In this talk I will provide an overview of recent work from
the field of artificial intelligence on compact structured
representation of games.  In particular I will describe
graphical games, a structured form of normal form games, and
multiagent influence diagrams (MAIDs), a structured form of
extensive form games.  These representations unify data
structures from computer science with ideas from game theory
and allow the efficient description of very large games.
Over the past few years, they have received much attention
from the artificial intelligence community as possible
representations for large multiagent interactions.

One of the main directions of research regarding these
representations has been the use of structure in the game to
find equilibria efficiently.  I will review the recent work
on this topic, and then present recent work of Ben Blum,
Daphne Koller, and myself on algorithms that apply the
homotopy method of Govindan and Wilson to graphical games
and MAIDs, exploiting the structure of the games to vastly
improve computational time.