1. Artificial Intelligence in Game Design
Natural Language Understanding in Games

2. Natural Language in AI
Goal: User types or speaks sentences  AI “understands” well enough to
Change its knowledge
Formulate responses
Extremely difficult! Requires understanding of:
Sentence grammar
Context provided by other sentences and world in general
Motivation of speaker (are they lying, etc.)
Examples:
“Fred fired Joe.”
“Fred fired the cannon.”
“Fred fired Joe from the cannon.”

3. Natural Language in Games
Only input in old school text based adventure games
Player commands

4. Uses of Natural Language
One possible goal: Providing players a “realistic” way to interact with human-type NPCs
Key: Restrict to limited domain
NPC has specific purpose in game
Player understands that purpose
Player specifically tailors sentences towards that specific purpose
Example: “Shopkeeper” character
Player wants to find out what they have
Player wants to negotiate prices

5. Keyword Search Classify sentences based on certain words it contains
Produce appropriate response based on sentence classification
Canned sentence
Action
Character state change
First implementation: Eliza “automated therapist”
Input sentences
Response sentence produced
Key: Limited domain
Produced type of feedback people expected from “Counselor Troi” type of psychobabble

6. Eliza
User input
Eliza responses

7. Eliza Classified typically expected words into categories
Synonyms
Words that should have same response
Chose a corresponding response sentence at random
Example: “family” sentences

8. Eliza Often echoes back phrases entered by user to appear less canned
“can you ______”  “You want me to be able to _______?”

9. Eliza Key phrase to match
Echo back all words in sentence after the key phrase

10. Eliza Generated plausible “general prompts” if no keyword match
Much better than responding “I don’t understand”!

11. Colossal Cave Adventure
Keyword analysis of first two words in sentence
First word: verb
Second word: object on which verb acts

12. Colossal Cave Adventure
Keywords classified into categories

13. Colossal Cave Adventure
Subroutines implemented for word categories
Text files contain appropriate responses

14. Starship Titanic Game primarily based on simple language understanding
Players could “converse” with shipboard NPCs
Main purpose: “lead” player to tasks and goals

15. Starship Titanic Used keyword search
Had “random responses” if no match
Mistakes made plausible by game situation
Stated at beginning that all NPCs controlled by “damaged ship AI”

16. Shopkeeper Example Purpose: Sell potions and wands to player States:
Greet player and ask whether they would like to buy potion or wand
Find out which one
Haggle over price
Sell if agreed
Get angry if player leaves script or offers too low a price

17. Directed Conversation
Idea: Lead player into their role in the conversation
Make it possible to answer with one word responses
Make it clear what they are
Accept as many synonyms as possible
Basic structure like state machine
“Affirmative” keyword
Wand keyword
“Greetings! Would you like to buy something?”
“We have wands and potions. What would you like?”
Negotiation
Stage
Potion keyword
“Do you want a healing or a strength potion?”
Affirmative
yes, ok, sure, …
Healing or strength keyword

18. “Greetings! Would you like to buy something?”
Shortcuts
If sentence contains multiple keywords, use them all to speed up conversation
Example: “I’d like a strength potion”
Affirmative answer
Negotiation
Stage
“Greetings! Would you like to buy something?” …
Request for specific item

19. Confirmation Echo back phrases where possible
Makes things more interactive
Helps confirm that character understands what player wants
Example: “I’d like a strength potion”  “A strength potion costs 10 gp”
“We have wands and potions. What would you like?”
Wand keyword
Order = “wand”
“A Order costs 10 gold pieces. Would you
Like to buy it?”
Negotiation
Stage
Potion keyword
“Do you want a healing or a strength potion?”
Healing or strength keyword
Order = “strength potion” or “healing potion”

20. Memory Remember previous player interactions
Use to shortcut process and simplify play
Makes NPC appear more intelligent
Done by some versions of Eliza
“Affirmative” keyword
Player enters shop
“Welcome back! Would you like another Order?”
Order != null
Order == null
“Negative” keyword
“We have wands and potions. What would you like?”
Wand keyword
Order = “wand”
“A Order costs 10 gold pieces. Would you
Like to buy it?”
Negotiation
Stage
Potion keyword
“Do you want a healing or a strength potion?”
Healing or strength keyword
Order = “strength potion” or “healing potion” 20

21. Responses
Character side of interaction should also be at appropriate level of detail
Descriptive when need to give player information
Terse when player should already have most information
Example: area descriptions in colossal cave (two different files)

22. Emotional States
Can use conversation to change emotional state of character
Example: Orc has “businesslike” and “angry” states
Possibly fuzzy (memberships in both)
Rules for changing membership:
Sentences orc can’t understand increases membership in Angry by 0.1
Incentive to stay on script!
Apologies increase membership in Businesslike by 0.1
Lowball offers in negotiations increase membership in Angry based on membership of offer in “low”
Good offers increase membership in Businesslike based on 1 - membership of offer in “low”
Businesslike
Angry

23. Emotional States
As with any emotional state, need way to express to player
Can choose actions as before
Membership in “Angry” > 0.8  Throw player out of shop
Can choose words based on state
Example: follow every response with “customer description”
Customer description based on membership in “Angry”
0.0 – 0.25
Sir, valued customer, …
0.25 – 0.5
<nothing>, customer
0.5 – 0.75
Annoying one, foolish one, …
0.8 – 1
<thrown out of shop>

24. Alternatives and Problems
Big question: Is it worth it?
Requires time
Requires large dictionary of synonyms even for limited domains
Requires handling of mistyped words
“I’d like a poiton”
Usual alternative: Choosing responses from menu
Limits responses
No haggling over prices!