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 Machine
Learning and Games - MALAGA
NIPS2007 Workshop - 8 December 2007, Whistler BC
This workshop will explore open directions in applying
machine learning to games.
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Description
Computer games sales are three time larger than industry software
sales, and on par with Hollywood box office sales; Halo 3 has become
the biggest entertainment launch in history, with $170 Million in
sales in the US alone in the first 24 hours! Modern computer
games are often based on extremely complex simulations of the real
world and constitute one of the very few real fields of application
for artificial intelligence encountered in everyday life.
Surprisingly, machine learning methods are not present in the vast
majority of computer games. There have been a few recent and notable
successes in turn-based two-player, discrete action space games such
as Backgammon, Checkers, Chess and Poker. However, these successes
are in stark contrast to the difficulties still encountered in the
majority of computer games, which typically involve more than two
agents choosing from a continuum of actions in complex artificial
environments. Typical game AI is still largely built around fixed
systems of rules that often result in implausible or predictable
behaviour and poor user experience. The purpose of this workshop is
to involve the NIPS community in the exciting challenges that games
- ranging from traditional table top games to cutting-edge console
and PC games - offer to machine learning.
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| Programme |
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9:00am |
Opening. Organizers |
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9:15am |
Decision Making and Knowledge Representation in
Halo 3
Max Dyckhoff, Bungie Studios |
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9:45am |
Computer (and Human) Perfection at Checkers
Jonathan Schaeffer, University of Alberta |
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10:15am |
Coffee break |
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10:30am |
State-of-the-Art in Computer Poker
Michael Bowling, University of Alberta |
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11:00am |
Monte-Carlo Planning for the Game of Go
Olivier Teytaud, TAO(Inria, Univ. Paris-Sud, UMR CNRS-8623) |
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11:30am |
Demos |
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12:00am |
Lunch Break |
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2:00pm |
Planning in Real-Time Strategy Games
Michael Buro, University of Alberta |
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2:30pm |
Learning Driving Tasks in TORCS Using Reinforcement Learning
A. Lazaric, D. Loiacono, A. Prete, M. Restelli, P.L. Lanzi,
Politecnico di Milano |
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2:50pm |
Modelling Go Positions with Planar CRFs
D. Kamenetsky, N. Schraudolph, S.Günter, S.V.N. Vishwanathan, NICTA |
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3:10pm |
Opportunities for Machine Learning to Impact Interactive Narrative
David L. Roberts, Mark Riedl, Charles L. Isbell, Georgia Institute of Technology |
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3:30pm |
Coffee break |
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3:45pm |
XNA Game Studio: Next-Gen Game Development at your
Fingertips
Chris Satchell, Microsoft |
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4:15pm |
Panel discussion
Invited panelist: Luis von Ahn, Carnegie Mellon University |
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Invited Speakers
- Max Dyckhoff, Bungie Studios. Programmed the
AI of Halo
3, the most highly anticipated computer game ever. Within 24
hours of release, Halo 3 generated
$170m in sales in the United States alone.
- Chris Satchell, XNA Group. The man behind
“XNA Game Studio”, a development environment for game development intended for students, hobbyist and independent game developers. A number of academic institutions have already agreed to include XNA Game Studio in their course offerings.
- Jonathan Schaeffer, University of Alberta.
Lead-creator of Chinook,
the world man-machine Checkers champion: the first program to win a human championship in any
popular board game. More recently he
solved the game of Checkers.
- Michael Bowling, University of Alberta.
Head of the University of Alberta computer Poker group and part of
the team that won the bankroll and the series competitions at the
2006 AAAI Computer Poker Competition,
and the limit online and limit equilibrium series at the
2007 AAAI Computer
Poker Competition.
- Sylvain Gelly,
Google.
Co-creator of the Go program MoGo, winner of six Kiseido Go Server (KGS) tournaments and considered one of the best programs in the world.
- Michael Buro, University of Alberta. Expert in
Real-Time Strategy (RTS) Game AI, creator of the
ORTS Game Engine.
Michael is also the author of the computer Othello player
Logistello,
unbeaten between 1993 and 1997.
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Demos
- Learning to drive by Reinforcement Learning. Phillip Trelford,
MSRC.
Interactive demo showing the AMPS reinforcement learning framework integrated into the state of the art
car racing game,
Project Gotham Racing
3 (PGR3).
- Checkers. Jonathan Schaeffer, University of
Alberta.
Playable demo of the perfect checkers player,
which is the result of the recent
solution of the game after almost 20 years
of computation!
- MoGo: Monte Carlo Go. Sylvain Gelly,
Google.
Opportunity to witness and play against one of the strongest currently available Go programs based on
Monte-Carlo search.
- Polaris: Computer Poker. Michael Bowling,
University of Alberta.
Chance to match your wits against the first poker computer player ever to
challenge top human professional players.
- Halo 3 AI. Max Dyckhoff,
Bungie Studios.
Display of the inner workings of the
Artificial Intelligence driving the Earth threatening covenants
in the blockbuster game Halo 3.
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Panel Discussion
We will devote at least one hour of the workshop to a panel
discussion. The panel will be composed of the invited speakers, plus
as a special guest, the speaker of the NIPS 2007 opening night banquet:
- Luis von Ahn, Carnegie Mellon University.
Expert in human computation; inventor of games such as
the ESP game for
image labelling to make use of human brain cycles.
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Summary Video
We have compiled a summary video which you can download here. The video is about
2 minutes long, encoded in Windows Media Format 6 MB large in file size. Enjoy!
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