2. Graduate Capstone Project Breaking Walls: Developing a Successful Robot in Robocode Chris Velez cvelez4@pride.hofstra.edu Summer 2011 Advisor :Dr. Xiang Fu Committee Members: Dr. Habib Ammari, Dr. Chuck Liang 1

3. Overview Introduction Problem Algorithm Design Performance Conclusion 2

4. What is Robocode? Game where robots battle in an arena Robots are controlled via Java programs Battles consists of 10 rounds A battle ends when robot is destroyed 3

5. Anatomy of a Robot 4

6. The Problem Goal: Defeat the robotWalls Walls is the top performing robot Must create a robot to defeat Walls 5

7. The WallsKiller Robot Contribution: Creation of WallsKiller WallsKiller defeats Walls in 1 on 1 combat. Maintains a high level of performance 6

8. What Does WallsKiller do? Implements a firing algorithm developed to hit Walls Uses an erratic movement pattern to avoid enemy fire 7

9. The Algorithm Takes advantages of Walls predictable movements Predicts the movements of the Walls robot Uses quadratic equations 8

10. Walls Behavior 9

11. The Cosine Rule Will utilize rule and apply to the positions of Walls and Wallskiller 10

12. Applying Cosine Rule 11 Alpha Beta

13. Design WallsKillerRobot BattleData FireControlSystem FireCommand QuadraticEqRoots 12

14. 13

15. WallsKillerRobot Base class Controls movement and firing commands Battle event handlers 14

16. BattleData X,Y – Coordinate data Distance, heading and bearing Enemy heading, bearing and velocity 15

17. FireControlSystem Implements firing algorithm Calculates firing angle Passes information to FireCommand 16

18. FireCommand Choose whether or not to fire Set power of bullets Determines degrees to rotate gun 17

19. QuadraticEqRoots Implementes advanced mathematics Returns data to FireControlSystem 18

20. Performance Hit Rate 70% Average Remaining Health: 77 Energy Robocode Score: 72% 19

21. Observations Hit percentage under 100% Walls turning Improved evasion 20

22. Conclusion Successful in 1-on-1 combat Performance shows room for improvement Needs improved movement algorithm 21

23. References Mathew Nelson, "Robocode", available at http://robocode.sourceforge.net/, retrieved 06/01/2009. Parker S, “Secrets from the Robocode Masters: Predictive Targeting”, http://www.imb.com/developerworks/java/library/j-pred-targeting/ (2002) Eisenstein, J.: “Evolving robocode tank fighters”. Technical Report AIM- 2003-023, AI Lab, Massachuesetts Institute of Technology (2003) F.N. Larsend, “Robocode Scoring” Available: http://robowiki.net/wiki/Robocode/Scoring (2010) S.Li,“Rock‘em sock ‘em robocode!, http://www.ibm.com/developerworks/java/library/j-robocode/ (2002) 22

24. References cont. Shichel S, Ziserman E, Sipper M,: “GP-Robocode: Using genetic programming to evolve robocode players”. Ben-Gurion University, Department of Computer Science. Kobayashi K, Uchida Y, Wantabe K,: “A study of Battle Stragety for Robocode”. SIC Annual Conference, Fubuki University Japan (2003) J.L Nielson and B.F Jensen, “Modern AI for Games: Robocode”. http://www.jonnielson.net/RoboReportOfficial.pdf, (2010) J. Hong and S. Cho, “Evolution of emergent behaviors for shooting game characters in Robocode,” Evolutionary Computation, pp. 634- 638, 2004 23