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

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Presentation on theme: "How to Teach Game AI from Scratch Brian Magerko, Ph.D. Assistant Professor of Digital Media Georgia Tech."— Presentation transcript:

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

10

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

21

22

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!


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