1. Artificial Intelligence in Game Design
Goal-Oriented Action Planning

2. Goals Complex characters have goals What if goals conflict?
Actions appear motivated instead of reflexive
Player must be aware of character motivations
Example: Napoleon “boss” NPC
Capture other cities
Protect own cities
Increase gold level
What if goals conflict?
Get gold
Avoid player
???

3. Goals and the Sims Overall goals for player to meet
Positive and negative goals
Transient goals based on physical needs
Hunger
Energy
Fun
Etc.
Characters automatically choose actions to meet needs

4. Goals and Actions Goals have actions than fulfill need
Key questions: Which actions should NPC take to fulfill which goals?
Hunger
Eat snack
Cook dinner
Energy
Nap in chair
Sleep in bed
Fun
Go to concert
Paint
Read

5. Insistence of Needs Needs may have “degree of urgency” (insistence)
How critical is need?
How important is this need relative to others?
How much of an action is needed to fulfill need?
Represented as number
Higher = greater need
Zero = no need
Need
Insistence
Hunger 5
Energy
Fun 3

6. Actions and Goals Actions can permanently fulfill goals
Replaced with another related goal (Sims)
Ends game (Napoleon captures all cities in world)
Actions can temporarily lessen needs
Action: Need – n (lessens that need by n)
Hunger
Eat snack: Hunger – 1
Cook dinner: Hunger – 5
Energy
Nap in chair: Energy – 1
Sleep in bed: Energy – 5
Fun
Go to concert: Fun – 4
Paint: Fun – 2
Read: Fun – 1

7. Choosing Actions Simple approach: Choose goal with highest insistence
Choose action that gives largest decrease
Need
Insistence
Hunger 6
Energy
Fun 3
Greatest need
Best action
Eat
Eat snack: Hunger – 1
Cook dinner: Hunger – 5
Energy
Nap in chair: Energy – 1
Sleep in bed: Energy – 5
Fun
Go to concert: Fun – 4
Paint: Fun – 2

8. Side Effects Actions can effect multiple goals Side effect
Drink Coffee
Hunger – 1
Energy – 1
Eat at Restaurant
Hunger – 4
Fun – 3
Cook Gourmet Meal
Hunger – 5
Fun – 1
Energy + 1
Side effect
Fulfilling one goal increases other needs

9. Overall Utility Utility-based decision making
Determine effect of each action on total needs
Choose action that has best overall effect
One criteria: sum of all needs
Need
Current level
After Cook Gourmet Meal
After Drink Coffee
After Eat at Restaurant
After Sleep in Bed
Hunger 3 2
Energy 1
Fun 4
Total effect 6 7
Best action

10. Overall Utility Problem: This can ignore very severe needs
Behavior does not appear rational!
Need
Current level
After Eat at Restaurant
After Sleep in Bed
Hunger 3
Energy 10 5
Fun
Total effect 11
Will be chosen, even though Sim is very tired!

11. Overall Squared Utility
Common solution: Total discontentment = sum of square of needs
Need
Current level
After Eat at Restaurant
After Sleep in Bed
Hunger 3 02 32
Energy 10
102 52
Fun
Total effect
100 43

12. Planning Creating series of actions to meet some goal
Planning actions to meet multiple needs
Chosen so final state has highest utility
Intermediate states after part of sequence should not be unacceptable
Allows fast actions to be chosen in logical circumstances
Planning actions with multiple steps before payoff
Purchase ingredients
Cook ingredients in oven
Eat meal
No effect on hunger until after last step

13. Planning Example 85 81 107 169 Best action if single action allowed
Effect on Fun
Effect on Energy
Paint -2 +1
Go to Concert -9 +3
Nap in Chair
Sleep in Bed +5
-10
Need
Current level
After Paint
After Go to Concert
After Nap in Chair
After Sleep in Bed
Fun 8 62 02 92
132
Energy 6 72 42
Total effect
100 85 81
107
169
Best action if single action allowed
Will be very tired afterward!

14. Planning Example Better approach for two large needs: Example: 107 49
Take fast action to relieve one
Then take another action to relieve other
Example:
Take nap before concert
Need
Current level
After Nap in Chair
Then After Go to Concert
Fun 8 92 02
Energy 6 42 72
Total effect
100
107 49
Better than taking single action

15. Planning and Search Trees
Must try all possible combinations of actions
Compute total discontentment for each path
Choose path with lowest total
root
Paint
Go to Concert
Nap in Chair
Sleep in Bed
Paint
Paint
Go to Concert
Paint
Nap in Chair
Paint
Sleep in Bed
Nap in Chair
Paint
Nap in Chair
Go to Concert
Nap in Chair
Nap in Chair
Sleep in Bed
Go to Concert
Paint
Go to Concert
Go to Concert
Nap in Chair
Go to Concert
Sleep in Bed
Sleep in Bed
Paint
Sleep in Bed
Go to Concert
Sleep in Bed
Nap in Chair
Sleep in Bed

16. Planning and Search Trees
an possible paths to test
Given a possible actions
Given n possible levels
Expanding search tree is costly
Will only be able to test small number of action combinations (lookahead limit)
Even two actions enough to seem intelligent
Looks like character thinking ahead

17. Planning and Search Trees
Algorithm: depth limited search
Depth-first search to some fixed limit n
an leafs in tree, so choose n so this can be computed in reasonable time
At each leaf, compute discontentment
Just keep track of best path found so far
Storage cost: n
Best sequence of actions found so far
Current path being tested

18. Pruning and Search Trees
Can cut off search down obviously bad branches
Branches with intermediate state unacceptably bad
Can possibly save search time (but no guarantee)
Character dead
No path can be better than best found so far, so no further search
Discontentment = 172