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AI Week 5

AI Week 5. GAM 224. Outline. Announcements Final Project Demos Discussion Break Lecture AI Narrative. Announcements. Advising week Game assignments available Readings reorganized a little for the new book. Final Project. Game concept document Parts Game overview Mechanics

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AI Week 5

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  1. AIWeek 5 GAM 224

  2. Outline • Announcements • Final Project • Demos • Discussion • Break • Lecture • AI • Narrative

  3. Announcements • Advising week • Game assignments available • Readings • reorganized a little for the new book

  4. Final Project • Game concept document • Parts • Game overview • Mechanics • Resources • Characters and Story • Sample Level

  5. Final Project 2 • Team project • 3 or 4 members • group authorship of overview • each member will be primary author of one other section

  6. Final Project 3 • 4 Milestones • 2/7 (next week) • Sort 9-12 game ideas • Adopt game idea • 2/21 • Design overview draft (3-4 pages) • Describe gameplay, context, key features. • Why would someone want to play it? • 2/28 • Resource inventory

  7. Homework #2

  8. Demos • Final Fantasy Tactics (Miranda) • Paper Mario (Bubon) • Fable (Summers) • Tales of Symphonia (Ballerini)

  9. AI • "Physics" of non-player characters • simulating the opponent • simulating other characters • In some games it is the whole point • classic strategy • Sims

  10. Artificial Intelligence • Broad field of study • 1950s: how to make computers think like people • Now • how to make computers less stupid

  11. Game AI • Uses very little from AI research • too slow • focused on different problems • Main issue • "planning" • how to get characters to act believably

  12. Planning • A planning problem • Current state • End state • Known operations • preconditions • postconditions • Construct • a sequence of operations to transform current state to end state

  13. Example • Current state • player is alive • End state • player is dead • Known operations • move around • use machete • precondition: must be near target • postcondition: target is dead

  14. Means-ends analysis • Work backwards from desired goal to current state • Example • to use machete, must be near player • to get near player, move • etc. • Problem • the world changes all the time

  15. Modern planning • Much more complex • Integration of • acting • sensing • choosing • prioritizing • etc. • Overkill for games

  16. Typical game AI tasks • Character behaviors • usually scripted actions • Route finding • many games • Resource management • in strategy games • Modeling character relationships • in some RPGs, some strategy games

  17. Goals for AI • Provide player with challenge • Make a good game experience • May go against "intelligence"

  18. Issues • Simulate or script? • as in physics • Opponent should not make obvious errors • Opponent should not be totally predictable

  19. Example • Simulation • when player is firing, construct a line-of-sight map from player's position. Find area outside of line-of-site especially if it is large and close • Script • have predefined "hiding" zones • when attacked go to the nearest location • In-between • have predefined "hiding" zones • calculate which is in the line-of-sight • go to closest • re-evaluate line-of-sight and move

  20. AI in design • Not too smart • Don't set expectations too high • Game play is more important • Not too dumb • Must cover minimum player expectations • Compensate • Level design • Resource advantages

  21. Action / Adventure • Demo • Lange: Splinter Cell: Pandora Tomorrow • Ingebrigsten: Grand Theft Auto: San Andreas • Pollard: Metal Gear Solid 3 • Hahn: Grim Fandango • Abero: Prince of Persia: Sands of Time • Non-demo • Entin: Myst • Reedy: Thief: Deadly Shadows • Devlin: The Suffering • Rojas: Prince of Persia: Warrior Within • Riordan: Grand Theft Auto III

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