1. How to Teach Game AI from Scratch Brian Magerko, Ph.D. Assistant Professor of Digital Media Georgia Tech

2. A Plethora of Programs ● Computational Media (B.S) ● Computer Science (B.S., M.S., Ph.D.) ● Digital Media (M.S., Ph.D.) ● Human-Centered Computing (Ph.D.)

3. Student Experience ● Motivation? ● Coding experience? ● AI background?

4. Course Design ● Appropriate abstraction for beginners & intermediates

5. Course Design ● Appropriate abstraction for beginners & intermediates ● Breadth of techniques

6. Course Design ● Appropriate abstraction for beginners & intermediates ● Breadth of techniques ● Algorithms / Aesthetics

7. spy party

8. prom week

9. party quirks AIIDE 2011; IVA 2011

11. Recommended Texts

12. Course Design ● Appropriate abstraction for beginners & intermediates ● Breadth of techniques ● Algorithms / Aesthetics ● Build early and consistently

13. Course Design ● Appropriate abstraction for beginners & intermediates ● Breadth of techniques ● Algorithms / Aesthetics ● Build early and consistently ● Focus on enabling soft skills

14. Soft Skills ● Problem identification ● Survey classes of approaches ● Matching solutions to problems ● Presenting rationale & work ● Working in teams

15. Project-based Learning

16. ● Lecture material tied to projects

17. Project-based Learning ● Lecture material tied to projects ● Uses free game AI resources

18. project 1

19. project 2

20. Google AI Challenge others

23. Project-based Learning ● Lecture material tied to projects ● Uses free game AI resources ● No algorithmic requirement

24. Project-based Learning ● Lecture material tied to projects ● Uses free game AI resources ● No algorithmic requirement ● Self-selected goal for project

25. Project-based Learning ● Lecture material tied to projects ● Uses free game AI resources ● No algorithmic requirement ● Self-selected goal for project ● Experimentation encouraged

26. Project-based Learning ● Lecture material tied to projects ● Uses free game AI resources ● No algorithmic requirement ● Self-selected goal for project ● Experimentation encouraged ● Process, product, and presentation are evaluated

27. Project-based Learning ● Lecture material tied to projects ● Uses free game AI resources ● No algorithmic requirement ● Self-selected goal for project ● Experimentation encouraged ● Process, product, and presentation are evaluated ● Community of practice

28. Final Project

29. ● Team project

30. Final Project ● Team project ● AI as Aesthetic vs. Board Game AI

31. Final Project ● Team project ● AI as Aesthetic vs. Board Game AI ● Open-ended requirements

32. Student Examples

33. mapstermind

34. zombies (h)ate my neighbors

35. mob mentality

36. ra

37. dominion

38. spy game

39. power grid

40. Takeaways ● Student-driven projects ● Focus on soft skills & breadth ● Make use of available environments ● Algorithms & Aesthetics

41. Thanks! magerko@gatech.edu http://lcc.gatech.edu/~bmagerko6 http://adam.cc.gatech.edu