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Game AI Kevin Dill Senior AI Engineer Blue Fang Games

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Presentation on theme: "Game AI Kevin Dill Senior AI Engineer Blue Fang Games"— Presentation transcript:

1 Game AI Kevin Dill Senior AI Engineer Blue Fang Games

2 Blue Fang Games “To create compelling, emotionally engaging games focused on the animal kingdom that set the benchmark for broad-based family entertainment.”

3 The Plan What is Game AI? How does it compare to Academic AI? A few common techniques A few interesting research areas NOTE: talk runs a little long

4 What is Game AI? Makes the characters in the game move Decide what, where, how, when Some uses of AI: –Opposing/allied player AI –Character AI –Path planning & collision avoidance –Animation selection

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6 The Goals of Game AI Games need to be fun! “Organic credibility” –Create the illusion of intelligence –Players will make up stories about the AI Rule #1: Don’t look stupid Rule #2: Try to look smart –But not *too* smart! Rule #3: Don’t cheat Rule #3 (revised): Don’t get caught!

7 Academic AI (vs. Game AI) Hard, unsolved problems Scientific method: Simplify & focus down –Planning Time Resources Imperfect knowledge Failure Not constrained by performance (mostly) –Checkers/Chess/Go

8 Game AI (vs. Academic AI) Avoid unsolved problems like the plague (unless it’s the core of your game) You can’t simplify the game away –Time –Resources –Imperfect knowledge –Failure *Very* constrained by performance

9 Techniques – Scripted AI AI Follows a script, much like a movie –Script specifies exactly what will happen, when it will happen, where it will happen Advantages: –Gives designers explicit control –Easy to write –Easy to balance Disadvantages –Extremely poor replayability

10 Techniques – State Machines States represent a high level view of what the AI is trying to do Each state has custom code Transitions occur when the situation changes

11 First Person Shooter Example Get Ammo Get Health Run Away Search For Enemy Attack Enemy Found Enemy Lost Low on Ammo Low on Health Got Away, Low on Health Got Health Got Ammo Got Away, Low on Ammo

12 Techniques – State Machines Advantages: –Easy to conceptualize –Easy to implement –Middleware tools exist Disadvantages: –Quickly becomes large and unwieldy Difficult to debug Difficult to expand –Rampant duplication of code

13 Techniques – Goal Based AI A “goal” is defined for every action that the AI can take Examples of goals from Kohan II include: Attack, Defend, Retreat, Explore, Build Each goal is assigned a priority, the highest priority goal(s) are executed

14 Explore Goal Example num_goals = 2min_priority = 0 base_priority = 300 repeat_penalty = 100 black_fog_priority = 500grey_fog_priority = 100 fog_search_depth = 3current_region_bonus = 200 actor_region_bonus = 100building_region_bonus = 50 flare_region_bonus = 1000 percent_to_count_region_explored = 0.8 consider_distance_to_kingdom_center = true kingdom_center_distance_prefer_close = true consider_distance_to_last_region = true last_region_distance_prefer_close = true consider_distance_to_actor = true actor_distance_prefer_close = true

15 Techniques – Goal Based AI Advantages –Flexible and powerful –Can execute more than one goal at a time –Emergent behavior Disadvantages: –Performance issues need to be managed –“Bucket of floats” can make balance tricky –Emergent behavior

16 Research – Path Planning *Not* a solved problem Particularly interesting is how to handle planning with constraints –Travel in forest is slower then open fields –Avoid being sighted by the enemy –*Really* avoid coming under enemy fire –See as much unexplored territory as possible

17 Research – Terrain Analysis How do I break the map up into meaningful areas? What use can I make of those areas? How can I launch a multi-pronged attack? How can I identify strategically important terrain to attack or defend? How can I identify my borders? What is the best placement for my scouts? Where can I ambush the enemy?

18 Research – Dynamic Difficulty Games need to be fun! How can I adjust game difficulty dynamically so as to deliver the proper challenge to the player? Is it possible to determine the challenge the player wants? Or does that have to be designer defined? How do I do all this without the player catching on?

19 Resources Artificial Intelligence for Games Ian Millington Programming Game AI by Example Matt Buckland AI Game Programming Wisdom 1-3 Steve Rabin, editor Craig Reynolds’ web site

20 Game AI Kevin Dill Senior AI Engineer Blue Fang Games


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