Slides about the competition including the results and the winner.

1. Institute of Computer Science
Chair of Cognitive Modeling
Demolition Derby 2012
Based on TORCS: The Open Racing Car Simulator
07/2012, Martin V. Butz

2. Demolition Derby 2012
http://cm.inf.uni-tuebingen.de/competitions
• Organized by:
- Martin V. Butz, University of Tübingen, Germany
• Supported by:
- Andreas Alin, University of Tübingen, Germany
- Dennis Schwartz, University of Tübingen, Germany
• And with previous help by:
- Matthias J. Linhardt, University of Bamberg, Germany
- Daniele Loiacono, Politecnico di Milano, Italy
- Luigi Cardamone, Politecnico di Milano, Italy
- Pier Luca Lanzi, Politecnico di Milano, Italy

3. Demolition Derby: Purpose
• Optimize opponent interactions
- Avoid being hit – run away when necessary
- Try to hit others at the right moment.
• Enables (co-)optimization of interaction behavior.
behavior
- Fitness may be based on damage caused to other cars.
- Co-development of two or more competitors is possible
(possibly with different approaches).
- Can do policy-gradient-based optimization
• Various strategy components are relevant
- Avoidance optimization
- Chasing others optimization
- Forwards & backwards steering control
- Opponent monitoring
- Meta-strategies
3

4. Goal & Setup
• Goal:
Wreck all opponent cars by
crashing into them without getting
wrecked yourself.
• Setup:
Local sensor information as in the Simulated Car Racing Competition.
• Sensors:
- Simulated distances sensors (noiseless).
 Surrounding 36 opponent sensors with a range of 300m.
 19 track sensors with a rang of 200m.
- Other sensors
 Current damage of own car.
 Damage produced on other cars.
 Status of car (speed, wheels, gear…).
 Relative position on track.
- Damage model:
 Cars do not take any damage when colliding with walls.
 Cars do not take any damage in the front when colliding with each other.
 Cars only take damage when their rear is hit by another car.
4

5. Winner Determination
• Arena: Large circular track (surface: asphalt; length: 640m, width: 90m)
Arena
• Qualifying
- 1-vs-1 matches evaluating all against all (winner = 1 point = less
damage)
- Eight best controllers qualify for the final showdown.
• Final demolition derby matches:
- The best eight controllers fight each other.
- Ten matches are played.
- Car that wins most often wins the competition.
- Alternative scoring with rank-based points is also considered.
5

6. Additional Goodies for a Quick Start
• Basic controller clients for Java and C++, to easily add additional
functionality.
• COBOSTAR client in Java
- With opponent monitor that tracks opponents over time.
- With simple crashing strategy that targets closest car in range.
• Evolvable client setup that
- receives caused damage signal,
- applies CMA evolution strategy-based optimization,
- runs continuously with or (even faster) without visualization for
as many generations as desired.

7. Last Years Entries
• Base Client
- Dep. of Computer Science
- University of Würzburg, Germany
• DemoStar
- Thies Lönneker, Dep. of Computer Science
- University of Würzburg, Germany
• Spartiat
- Zygmunt Horodyski, Piłsudskiego 39/1
- 66-530 Drezdenko, Poland

8. This Year’s NEW Entries
• JustDetermined
- Brian J Tellier
- University of Southern Maine (USM), Portland, ME, USA
USM
• KevinCar
- Kevin Knowlton
- University of Southern Maine (USM), Portland, ME, USA
USM
• SEALbot
- Anderson Rocha Tavares & Gabriel de Oliveira Ramos & Renato de
Pontes Pereira & Sérgio Montazzolli Silva & Ana L. C. Bazzan
- Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre,
UFRGS
Brasil
• SloppyJalopy
- David Gagne
- University of Southern Maine (USM), Portland, ME, USA
USM
• WSI-Client 2012
- Wilhelm-Schickard-Institut of Computer Science
- University of Tübingen, Germany
8 © 2012 University of Tuebingen

9. Last Year: Demo Star Approach
• Chase Opponent – try to crash
• Avoidance not considered.
• Challenges tackled:
- Opponent Tracking
 Use local distance sensors
 Also use global information (track location)
- DemoStar Agility:
 CMA-ES-based optimization of turning.
- DemoStar Recovery: Escape stuck situations
 Stuck Face-to-face
 Stuck at wall.
9 © 2012 University of Tuebingen

10. This Year: Strategy Improvements
• Simple approach from Uni Tübingen to increase the challenge:
- Modified Base-Client that avoids attacks early in the game
(“cowered car”).
Approaches by new entries:
• USM: Rule-based agents with higher-level rules and control
strategies:
- Conditions:
 Ahead, Close Ahead, Behind, Advantage, Edge, Wounded, No Change,
Duel, Turning
- Actions:
 Ram, Run, Bait, Get Clear, U-Turn, Circle Track
• UFRGS: Fuzzy rule-based agent:
- Four behavioral strategies:
 Stuck, Evade, Attack (front, side), Look for Opponents
- Scoring mechanism for selecting behavior and opponent
- Fuzzy rules make decisions
10 © 2012 University of Tuebingen

11. USM: Rule-based agents
JustDetermined
KevinCar
SloppyJalopy
11 © 2012 University of Tuebingen

12. USM Rule-Based Agents
 Agent behaviors are determined using a
rule-based approach
 No learning for the entries here, but this approach
is designed for EC learning
 Conditions and actions are drawn from a discrete
“vocabulary” of pre-designed options
 Each rule is a condition-action vector
 Conflict resolution:
 Rule order here (but specificity is usually helpful)
Gagne, Knowlton, Tellier, and Congdon, GECCO

13. USM Rule-Based Agents
 Abstractions interface between game and rules
 Low-level game sensors are abstracted to high-level rule
conditions
 High-level rule actions are translated to low-level game
controls
Game
low-level sensors controls low-level
details details
high-level inputs outputs high-level
abstractions Agent abstractions
conditions actions
Gagne, Knowlton, Tellier, and Congdon, GECCO

14. Conditions – Input Abstractions
Condition TRUE when…
Ahead
Ahead An enemy is ahead and within 100 m
Close Ahead Any enemy is ahead and within 20 m
Behind An enemy is behind and within 100 m Behind
Advantage Opponent has 2000 more damage than agent
Edge Agent is near the track edge
Wounded Agent has more than 7,000 damage
Agent has been doing the same thing
No Change
for a long time
Duel There is only one other opponent
Turning Agent has started a U-turn, but has not finished
Gagne, Knowlton, Algorithms Congdon, GECCO
Congdon, Genetic Tellier, and and NonCoding DNA

15. Actions – Output Abstractions as
Pictures
Action Pictorial Description
Ram Agent SMASH!
Run
Bait
Get Clear
U-Turn
Circle Track
Gagne, Knowlton, Tellier, and Congdon, GECCO

16. Actions – Output Abstractions in
English
Action Description
Ram • Steer toward opponent
• Slow down if necessary.
• Otherwise, full acceleration.
Run • Steer away from opponent
• Circle the track
• Full acceleration
Bait • Circle the track
• Speed limit 110 kph
• When opponent is close, swerve
Get Clear • Turn away from track edge
• If very close to edge, back up
U-Turn • Cut wheel hard left or right (coin flip)
• Keep wheel cut for 100 steps
Circle Track • Stay centered and in line with track axis
• Speed limit 110 kph
Gagne, Knowlton, Tellier, and Congdon, GECCO

17. Sloppy Jalopy Entry – Rule Set
Conditions Action
Ahead Close Behin Advantage Edge Wounded No Change Duel Turnin
Ahead d g
F * * * T * * * Get Clear
* * * F * F T * U-Turn
* * * * F T * F Run
* * * T F * * T Run
* * T * F F * F Bait
T * F * * * * F Ram
T * * * * F F T Ram
* * T F F * F T Bait
* * * * * * F * Circle Track
 ‘*’ Means any state satisfies this condition (Don’t Care).
 Grayed-out conditions are ignored by this agent.
Gagne, Knowlton, Tellier, and Congdon, GECCO

18. Sloppy Jalopy Behavior
 SJ runs away when it’s wounded or winning a
duel by a margin.
 Rams only when there is nobody behind it.
 Tries to score mainly by baiting opponents.
 Is more timid in multiplayer, more aggressive in a
duel.
 Does a U-Turn if it’s been doing one thing for a
while.
 Circle track by default.
Gagne, Knowlton, Tellier, and Congdon, GECCO

19. Crash and Segfault Entry – Rule Set
Conditions Action
Ahead Close Behin Advantage Edge Wounded No Change Duel Turnin
Ahead d g
F F * * T * * * * Get Clear
* F T * F * F * F Run
T F F T F * * * * Run
T F F F * * * * F Ram
F F F T F * * * * Circle
Track
* T * * * * * * * Ram
* F T * F * T * * U-Turn
F F F F F * F * F Circle
Track
F F F F F * T * * U-Turn
F F * F F * * * T U-Turn
 ‘*’ Means any state satisfies this condition (Don’t Care).
 Grayed-out conditions are ignored by this agent.
Gagne, Knowlton, Tellier, and Congdon, GECCO

20. Crash and Segfault Behavior
 Will always attempt to ram if an opponent is close
ahead.
 Runs away if an opponent is behind it.
 Runs away if it has a damage advantage in a
duel.
 Attempts to ram if there is an opponent ahead
and it isn't running.
 Will make a U-turn if it has gone a complete lap
around the track while either running or circling.
 If no other action is called for, will circle the track
to try to find opponents.
Gagne, Knowlton, Tellier, and Congdon, GECCO

21. JustDetermined Entry – Rule Set
Conditions Action
Ahead Close Behin Advantage Edge Wounded No Change Duel Turnin
Ahead d g
* * * * T * * * * Get Clear
* * T * * * * * * U-Turn
T * F * F * * * * Ram
* * F T F * * * * Run
F * F * F * * * * Circle Track
 ‘*’ Means any state satisfies this condition (Don’t Care).
 Grayed-out conditions are ignored by this agent.
Gagne, Knowlton, Tellier, and Congdon, GECCO

22. JustDetermined Behavior
 Basic wall detection to avoid walls
 Opponent is its main focus when opponent is in
front of the controller
 If an opponent is behind the controller, it will turn
around as fast as possible to hit the opponent
 When no opponent is near, the controller circles
the track to maintain speed
Gagne, Knowlton, Tellier, and Congdon, GECCO

23. Future Work
 Further evaluation of agents against a wider
variety of drivers.
 This basic approach is designed as a step
towards using EC on the rule sets.
 In addition to evolving the rule sets, parameters
such as “close” can benefit from EC to refine
these values.
Gagne, Knowlton, Tellier, and Congdon, GECCO

24. UFRGS: Fuzzy rule-based agent
SEAL-Bot
24 © 2012 University of Tuebingen

25. Results - Scoring
• Preliminary 1 vs. 1 Matches
- More matches won – participate in final showdown matches
- Eight qualify – therefore, all qualify (eight entries in total)
• Final showdown matches
- 10 matches
- Controller that wins the most matches wins the competition.
- Alternative point scoring also reported.
25 © 2012 University of Tuebingen

26. Preliminary 1 vs. 1 Matches
BaseClient WSI-Client 2012
BaseClient Spartiat Won WSI-Client 2012 BaseClient Won
BaseClient DemoStar Lost WSI-Client 2012 Spartiat Lost
BaseClient WSI-Client 2012 Lost WSI-Client 2012 DemoStar Tie
BaseClient KevinCar Lost WSI-Client 2012 KevinCar Lost SloppyJalopy
BaseClient SEALbot Lost WSI-Client 2012 SEALbot Tie SloppyJalopy BaseClient Lost
BaseClient SloppyJalopy Won WSI-Client 2012 SloppyJalopy Won
SloppyJalopy Spartiat Won
BaseClient JustDetermined Won WSI-Client 2012 JustDetermined Won
SloppyJalopy DemoStar Lost
Matches Won: 3 Matches Won: 3
SloppyJalopy WSI-Client 2012 Lost
Spartiat KevinCar SloppyJalopy KevinCar Lost
Spartiat BaseClient Lost KevinCar BaseClient Won SloppyJalopy SEALbot Tie
Spartiat DemoStar Tie KevinCar Spartiat Won SloppyJalopy JustDetermined Lost
Spartiat WSI-Client 2012 Won KevinCar DemoStar Won Matches Won: 1
Spartiat KevinCar Lost KevinCar WSI-Client 2012 Won
Spartiat SEALbot Lost KevinCar SEALbot Tie JustDetermined
Spartiat SloppyJalopy Lost KevinCar SloppyJalopy Won JustDetermined BaseClient Lost
Spartiat JustDetermined Won KevinCar JustDetermined Won Lost
JustDetermined Spartiat
Matches Won: 2 Matches Won: 6
JustDetermined DemoStar Tie
JustDetermined WSI-Client 2012 Lost
DemoStar SEALbot
Won JustDetermined KevinCar Lost
DemoStar BaseClient SEALbot BaseClient Won
DemoStar Spartiat Tie SEALbot Spartiat Won JustDetermined SEALbot Lost
DemoStar WSI-Client 2012 Tie SEALbot DemoStar Lost JustDetermined SloppyJalopy Won
DemoStar KevinCar Lost SEALbot WSI-Client 2012 Tie Matches Won: 1
DemoStar SEALbot Won SEALbot KevinCar Tie
DemoStar SloppyJalopy Won SEALbot SloppyJalopy Tie
DemoStar JustDetermined Tie SEALbot JustDetermined Won
Matches Won: 3 Matches Won 3
26 © 2012 University of Tuebingen

27. Preliminary 1 vs. 1 Matches
Ranking in Preliminaries….
1. KevinCar 6
2. BaseClient 3
DemoStar 3
SEALbot 3
WSI-Client 2012 3
6. Spartiat 2
7. SloppyJalopy 1
JustDetermined 1
27 © 2012 University of Tuebingen

28. Final Show-Down
• All eights controllers run against each other
• 10 runs.
• If one controllers is our (full damage) all other damages are reset
to zero!
• Results:
- Close but there is a clear winner…
28 © 2012 University of Tuebingen

29. 29 © 2012 University of Tuebingen

30. And the Winner is…
Run 1 Points Run 4 Run 7
1st WSI-Client 2012 7 1st SEALbot 7 1st KevinCar 7
2nd SloppyJalopy 6 2nd SloppyJalopy 6 2nd BaseClient 6
3rd SEALbot 5 3rd KevinCar 5 3rd SEALbot 5
4th KevinCar 4 4th DemoStar 4 4th WSI-Client 2012 4
5th BaseClient 3 5th WSI-Client 2012 3 5th SloppyJalopy 3
6th DemoStar 2 6th BaseClient 2 6th DemoStar 2
7th JustDetermined 1 7th JustDetermined 1 7th Spartiat 1
8th Spartiat 0 8th Spartiat 0 8th JustDetermined 0
Run 2 Run 5 Run 8
1st SEALbot 7 1st KevinCar 7 1st SEALbot 7
2nd BaseClient 6 2nd BaseClient 6 2nd SloppyJalopy 6
3rd WSI-Client 2012 5 3rd SEALbot 5 3rd BaseClient 5
4th KevinCar 4 4th SloppyJalopy 4 4th KevinCar 4
5th SloppyJalopy 3 5th WSI-Client 2012 3 5th DemoStar 3
6th JustDetermined 2 6th DemoStar 2 6th JustDetermined 2
7th Spartiat 1 7th Spartiat 1 7th Spartiat 1
8th DemoStar 0 8th JustDetermined 0 8th WSI-Client 2012 0
Run 3 Run 6 Points Run 9
1st JustDetermined 7 1st BaseClient 7 1st SEALbot 7
2nd KevinCar 6 2nd SloppyJalopy 6 2nd SloppyJalopy 6
3rd SloppyJalopy 5 3rd DemoStar 5 3rd WSI-Client 2012 5
4th WSI-Client 2012 4 4th JustDetermined 4 4th DemoStar 4
5th DemoStar 3 5th SEALbot 3 5th Spartiat 3
6th BaseClient 2 6th Spartiat 2 6th KevinCar 2
7th Spartiat 1 7th WSI-Client 2012 1 7th BaseClient 1
8th SEALbot 0 8th KevinCar 0 8th JustDetermined 0
30 © 2012 University of Tuebingen

31. And the Winner is…
Run 1 Points Run 4 Run 7
1st WSI-Client 2012 7 1st SEALbot 7 1st KevinCar 7
2nd SloppyJalopy 6 2nd SloppyJalopy 6 2nd BaseClient 6
3rd SEALbot 5 3rd KevinCar 5 3rd SEALbot 5
4th KevinCar 4 4th DemoStar 4 4th WSI-Client 2012 4
5th BaseClient 3 5th WSI-Client 2012 3 5th SloppyJalopy 3
6th DemoStar 2 6th BaseClient 2 6th DemoStar 2
7th JustDetermined 1 7th JustDetermined 1 7th Spartiat 1
8th Spartiat 0 8th Spartiat 0 8th JustDetermined 0
Run 10
Run 2 Run 5 Run 8
1st SEALbot 7
1st SEALbot 7 1st KevinCar 7 1st SEALbot 7
2nd JustDetermined 6 2nd SloppyJalopy 6
2nd BaseClient 6 2nd BaseClient 6
3rd WSI-Client 2012 5 3rd3rd SloppyJalopy
SEALbot 5 5 3rd BaseClient 5
4th KevinCar 4 4th4th SloppyJalopy
KevinCar 4 4 4th KevinCar 4
5th SloppyJalopy 3 5th5th WSI-Client 2012
WSI-Client 2012 3 3 5th DemoStar 3
6th JustDetermined 2 6th DemoStar 2 6th JustDetermined 2
6th BaseClient 2
7th Spartiat 1 7th Spartiat 1 7th Spartiat 1
7th Spartiat 1
8th DemoStar 0 8th JustDetermined 0 8th WSI-Client 2012 0
8th DemoStar 0
Run 3 Run 6 Points Run 9
1st JustDetermined 7 1st BaseClient 7 1st SEALbot 7
2nd KevinCar 6 2nd SloppyJalopy 6 2nd SloppyJalopy 6
3rd SloppyJalopy 5 3rd DemoStar 5 3rd WSI-Client 2012 5
4th WSI-Client 2012 4 4th JustDetermined 4 4th DemoStar 4
5th DemoStar 3 5th SEALbot 3 5th Spartiat 3
6th BaseClient 2 6th Spartiat 2 6th KevinCar 2
7th Spartiat 1 7th WSI-Client 2012 1 7th BaseClient 1
8th SEALbot 0 8th KevinCar 0 8th JustDetermined 0
31 © 2012 University of Tuebingen

32. And the Winner is....
SEALbot
Anderson Rocha Tavares
Anderson Rocha Tavares & Gabriel de Oliveira Ramos & Renato
de Pontes Pereira & Sérgio Montazzolli Silva & Ana L. C. Bazzan
Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre
UFRGS
Brasil

33. Final Scores and Rankings
Rank Name # of Wins Points
1 SEALbot 5 53
3 KevinCar 2 43
4 BaseClient 1 40
5 WSI-Client 2012 1 35
6 JustDetermined 1 32
2 SloppyJalopy 0 50
7 DemoStar 0 25
8 Spartiat 0 11
33 © 2012 University of Tuebingen

34. Institute of Computer Science
Chair of Cognitive Modeling
Thank you for the
attention!