Artificial Intelligence in
Game Design
Lecture 17:
Goal Oriented Action Planning
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
Planning Example
Action
Effect on Fun
Effect on Energy
Paint
-2
+1
Go to Concert
-9
+3
Nap in Chair
+1
-2
Sleep in Bed
+5
-10
Need
Current
level
After Paint
After Go to After Nap
Concert
in Chair
After Sleep
in Bed
Fun
8
62
02
92
132
Energy
6
72
92
42
02
100
85
81
107
169
Total effect
Best action if single action allowed
Will be very tired afterward!
Planning Example
• Better approach for two large needs:
– 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
100
107
49
Total effect
Better than taking
single action
Planning and Utility
• Why choose this order?
– Why take nap before concert instead of going to concert first?
• Goal: Minimize “total discontentment” over time
Σ discontentment at time t
t
Need
Time 0
Fun
8
52
22
02
12
Energy
6
72
82
92
72
Total
100
74
68
81
50
Need
Time 0
Total
discontentment:
Fun
8
92
62
32
02
240
Energy
6
42
52
62
72
100
85
61
45
49
Total
discontentment:
273
Total
Time 1
(concert)
Time 1
(nap)
Time 2
(concert)
Time 2
(concert)
Time 3
(concert)
Time 3
(concert)
Time 4
(nap)
Time 4
(concert)
Planning and Search Trees
• Must try all possible combinations of actions
– Compute total discontentment for each path
– Choose path with lowest total
root
Go to
Concert
Paint
Paint
Paint
Paint
Go to
Conc
ert
Nap
in
Chair
Sleep
in
Bed
Nap
in
Chair
Paint
Paint
Paint
Go to
Conc
ert
Paint
Nap in
Chair
Go to
Conc
ert
Go to
Conc
ert
Go to
Conc
ert
Nap
in
Chair
Go to
Conc
ert
Sleep
in
Bed
Nap
in
Chair
Go to
Conc
ert
Nap
in
Chair
Nap
in
Chair
Sleep in
Bed
Nap
in
Chair
Sleep
in
Bed
Sleep
in
Bed
Paint
Sleep
in
Bed
Go to
Conc
ert
Sleep
in
Bed
Nap
in
Chair
Sleep
in
Bed
Sleep
in
Bed
Planning and Search Trees
• Expanding search tree is costly
– Given a possible actions
– Given n possible levels
• an possibilities to test
– 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
Planning and Search Trees
• Algorithm: depth limited search
– Depth-first search to some fixed limit n
•
an leafs in tree
– At each leaf, compute total discontentment
– Just keep track of best path found so far
• Storage cost: n
Best sequence of
actions found so far
Current path
being tested
Pruning and Search Trees
• Can cut off search down obviously bad branches
– Branches with intermediate state unacceptably bad
– Branches with total discontentment more than best sequence found so
far
– Can possibly save search time (but no guarantee)
Discontentment at this
state= 150
Total discontentment to
this point = 180
Total
discontentment
= 172
No path can be better
than best found so far,
so no further search
Unacceptably bad, so
no further search
Planning and Preconditions
• Actions may have preconditions before they can be taken
Preconditions
Action
Postconditions
• Multiple actions required to meet needs
Preconditions which
character meets
Action
Postconditions
meets
Preconditions
Action
Postconditions
meet need
Planning and Preconditions
• Example: Microwaving food
Uncooked food
in fridge
Get food
Have uncooked
food
meets
Have uncooked food
Have microwave
Cook food in
microwave
Have cooked
food
meets
Have cooked
food
Eat food
Hunger - 5
Planning Methods
• Depth-limited search
– Try all combinations of actions up to lookahead limit
– Can prune branches with actions whose preconditions not met
Get food
Cook food in
microwave
Prerequisite not met
Cook food in
microwave
• Expensive
– Design world so actions require few steps (2 or 3 at most)
Planning Methods
• Scripted action sequences
– Actually single action with what appears to be multiple steps
– Long animated sequence
Have uncooked food
Have microwave
Get food
Cook food in microwave
Eat food
Hungry - 5
• Very simple to implement (no planning needed!)
• Weaknesses:
– Cannot interrupt sequence without starting over entirely
• Phone rings while cooking
– Cannot start plan until all preconditions met
Opportunistic Planning
• What if not all preconditions for plan exist?
– Can get uncooked food
– No microwave to cook food (yet)
– Should still buy the food if hungry!
• Opportunistic planning:
Taking actions which may pay off in future
– Meets one of several prerequisites for action
Have uncooked food
Have microwave
Get food from fridge
Cook food in microwave
Eat food
Hungry - 5
– Other prerequisites can then become goals for character
• Tell player to buy microwave for character
• Search for microwave…