1. Artificial Intelligence in Game Design
Intelligent Decision Making and Decision Trees

2. Decision Making Based on internal and external information
Defines a current action (“eat food”)
Changes world and internal state
“I am hungry”
“There is food nearby”
“Food nearby is gone”
“I am not hungry”

3. “Intelligent Agent” Approach
Reflex agent No memory, just “if-then” rules
Memory-based agent Also based on current state
Goal-based agent Chooses actions that best help meet current goal
Utility-based agent Balances multiple weighted goals, choosing actions that give best overall state
action
input
rules
action
input
rules
memory
Goal-based planning
Sims

4. Reflex Agents
Example: “orc” reflex agent if hitPoints < 5 then run away from player if distance to player < 2 units then attack player if player visible the run towards player else move in random direction

5. Reflex Agents
Example: “orc” reflex agent if hitPoints < 5 then run away from player if distance to player < 2 units then attack player if player visible then run towards player else move in random direction
Internal state
External state

6. Reflex Agents
Actions often hierarchical if hitPoints < 5 then run away from player if distance to player < 2 units then attack player if player visible then run towards player else move in random direction
These will call complex navigation subroutines to implement the action

7. Reflex Agents
Must consider cost of gathering inputs if hitPoints < 5 then run away from player if distance to player < 2 units then attack player if player visible if player in same room or distance to player < 5 units then run towards player else move in random direction
This requires complex computations

8. Reflex Agents Possible problem: Multiple rules may fire
Indicated actions may be contradictory
Action may depend on order of rules
Problem if rules added by multiple developers (side effects)
if hitPoints < 5 then run away from player if distance to player < 2 units then attack player
What if next to player and have low hit points?

9. Within one unit of player?
Decision Trees
Simple decision tool
Easy for non-programmers to understand
No ambiguity
Very efficient
Simple tree traversal
Node = question
Branch to follow = answer
Leaf = final action to take
Hit points < 5? no
yes
Obstacle between
myself and player?
Within one unit of player?
yes
yes no no
Path to player clear?
hide
run
attack
yes no
run towards player
run sideways

10. Randomness in Decision Trees
Make decisions at some nodes based on random number
Math.random() < 0.5
yes no
defend
Math.random() < 0.2
yes no
Swing sword from left
Swing sword from right

11. Randomness in Decision Trees
Problem: Generating different random action may not be plausible
Will both stand still and patrol for a few frames at a time
Better if it decided to do one and keep doing it for a while
Need states to implement this idea
Math.random() < 0.4
yes no
Stand still
Patrol