Is it Possible to Build
Dramatically Compelling Interactive
Games?
Digital Entertainment?
v2
Selmer Bringsjord
Director, Minds & Machines Laboratory
Prof of Logic and Cognitive Science
Dept. of Philosophy, Psychology & Cognitive Science
Department of Computer Science
Rensselaer Polytechnic Institute (RPI)
Troy NY 12180 USA
Chief Scientist, Document Development Corporation
1223 Peoples Ave. Troy NY 12180 USA
selmer@rpi.edu
http://www.rpi.edu/~brings
Is it Possible to Build
Dramatically Compelling Interactive
Digital Entertainment?
Selmer Bringsjord
Director, Minds & Machines Laboratory
Prof of Logic, Cognitive Science, & Computer Science
Dept. of Philosophy, Psychology & Cognitive Science
Department of Computer Science
Rensselaer Polytechnic Institute (RPI)
Troy NY 12180 USA
Chief Scientist, Document Development Corporation
1223 Peoples Ave. Troy NY 12180 USA
selmer@rpi.edu
http://www.rpi.edu/~brings
Is it Possible to Build
Dramatically Compelling Interactive
Digital Entertainment?
Selmer Bringsjord
Director, Minds & Machines Laboratory
Prof of Logic, Cognitive Science, & Computer Science
Dept. of Philosophy, Psychology & Cognitive Science
Department of Computer Science
Rensselaer Polytechnic Institute (RPI)
Troy NY 12180 USA
Chief Scientist, Document Development Corporation
1223 Peoples Ave. Troy NY 12180 USA
selmer@rpi.edu
http://www.rpi.edu/~brings
We Have Dramatically Compelling
Digital Entertainment
Two Preliminary Points
• Mathematically-based realism about AI (and, in
this case, narrative)
– Solvable vs Unsolvable Problems
• Computers aren’t finite diagrams or finite state automata, but
rather LBAs or Turing machines, and as such are impotent in
the face of an infinite number of problems
• There’s no free lunch
– Automated learning isn’t going to give us great NPC’s
– Laird
– Ergo, Logic!
Logical Systems: Which for DCIDE?
Name
Alphabet
Grammar
Proof
Theory
Semantics
Metatheory
LPC
p, q, r, … and
truthfunctional
connectives
Easy
Fitch-style and
natural
deduction,
resolution, etc.
Truth tables!
Sound,
complete,
compact,
decidable
Add variables
x, y, … and 

Easy
Fitch-style and
natural
deduction,
resolution, e.g.
Structures and
interpretations
Sound,
complete,
compact,
undecidable
LPML
Add “box” and
“diamond” for
necessity and
possibility
Wffs created
by prefixing
new operators
to wffs
Add
necessitation,
etc.
Possible
worlds
Similar to
LPC
LII
New variables
for predicates
Pretty obvious
New adapt
quantifier
rules
Quantification
over subsets in
domain
allowed
Sound but not
complete
Propositional Calculus
LI
First-Order Logic
Unfortunately…
Name
Alphabet
Grammar
Proof
Theory
Semantics
Metatheory
LPC
p, q, r, … and
truthfunctional
connectives
Easy
Fitch-style and
natural
deduction,
resolution, etc.
Truth tables!
Sound,
complete,
compact,
decidable
Add variables
x, y, … and 

Easy
Fitch-style and
natural
deduction,
resolution, e.g.
Structures and
interpretations
Sound,
complete,
compact,
undecidable
LPML
Add “box” and
“diamond” for
necessity and
possibility
Wffs created
by prefixing
new operators
to wffs
Add
necessitation,
etc.
Possible
worlds
Similar to
LPC
LII
New variables
for predicates
Pretty obvious
New adapt
quantifier
rules
Quantification
over subsets in
domain
allowed
Sound but not
complete
Propositional Calculus
LI
First-Order Logic
Some Key Challenges
• Formalizing Literary Themes
– For me it’s been betrayal
– Coming: mendacity
– “Selmer, we want X in our game.”
• Well, I need some serious money for that.
• Story Mastery
– Without it, hack-and-slash, at best
– The Bates experiment
– Fortunes to be made here
• Building Robust Autonomous Characters
• Personalization
Mendacity
Autonomous AI in The Matrix
Characters Must Be
Intelligent Agents
Generic Knowledge-Based Agent
(smarter than what appear in nearly all games,
including, e.g., Hitman)
function KB-Agent(percept) returns an action
inputs: p, a percept
static: KB, a knowledge base
t, a counter, initially 0
Tell(KB, Make-Percept-Sentence(percept, t))
action  Ask(KB, Make-Action-Query(t))
Tell(KB, Make-Action-Sentence(action, t))
tt+1
return action
The Wumpus World
We Build Agents Like This in the
Minds & Machines Laboratory
But Personhood Involves…
•
•
•
•
Ability to communicate in a language
today
Autonomy (“free will”)
Creativity
Phenomenal consciousness (= subjective
awareness, qualia, what-it’s-like-to-be-you
consciousness, P-consciousness)
• Robust abstract reasoning
Turing Test
Judge
What color and in what
style is your hair?
In the TT, it’s Really Judge vs. Designer
I can handle tha- uh, it
can handle that one.
Judge
What color and in what
style is your hair?
Designer
The Lovelace Test
How did it do that?
S
o
Designer (= Judge)
Judge (= Designer)
Definition of Lovelace Test
• Artificial agent A, designed by H, passes LT if and
only if
– A outputs o;
– A’s outputting o is not the result of a fluke hardware
error, but rather the result of processes A can repeat;
– H (or someone who knows what H knows, and has H’s
resources) cannot explain how A produced o by appeal
to A’s architecture, knowledge-base, and core functions.
What Systems Fail LT?
• Brutus (see final chapter)
• Copycat (see book as well)
• Letter Spirit
.
.
.
Is the Set of All “A”s Countable?
The Original Dream
ABCDEF…Z
Percepts: ?
Actions:
Design remaining
letters
Letter Spirit System as an
Intelligent Agent
Letter Spirit
ABC
Percepts:
seed letters
DEF…Z
Actions:
Design remaining
letters
Step #1
• Digitize!
– Figure X-5
• Ten human-designed gridfonts (Fig X-6)
• 1500 A’s (Fig X-7)
• Okay, now how does this work?…
The Retreat to Grids
Ten Human-Designed Gridfonts
1500 “A”s are Possible
The Argument That Worries Me
1 Dramatically compelling interactive digital entertainment
requires the presence in such entertainment of virtual
persons, and therefore requires the presence of autonomous
virtual characters.
2 Autonomous virtual characters would pass the Lovelace
Test.
3 Autonomous virtual characters would be intelligent agents,
in the technical sense of “intelligent agents” in use in AI
(specifically in AIMA).
4 Intelligent agents fail the Lovelace Test.
Therefore:
5 Dramatically compelling interactive digital entertainment
isn't possible.
Again: I Want to Administer the
Turing Test in a Digital World…
But my argument indicates
that for this dream to become
reality will require some
preternaturally clever engineering.
Toward Mendacity
• x tells lie p to y iff
– p is false;
– x knows that p is false;
Toward Mendacity
• x tells lie p to y iff
– p is false;
– x knows that p is false;
• But where’s the communication?
Toward Mendacity
• x tells lie p to y iff
– x (in some technical communicative sense) tells
y p;
• (Using AIMA, we could invoke TELLing to
another’s KB)
– p is false;
– x knows that p is false;
Toward Mendacity
• x tells lie p to y iff
– x (in some technical communicative sense) tells
y p;
• (Using AIMA, we could invoke TELLing to
another’s KB)
– p is false;
– x knows that p is false;
• But perhaps x is being sarcastic!
Toward Mendacity
• x tells lie p to y iff
– x (in some technical communicative sense) tells
y p;
• (Using AIMA, we could invoke TELLing to
another’s KB)
– p is false;
– x knows that p is false;
– x wants y to believe p.
Toward Mendacity
• x tells lie p to y iff
– x (in some technical communicative sense) tells y p;
• (Using AIMA, we could invoke TELLing to another’s KB)
– p is false;
– x knows that p is false;
– x wants y to believe p.
• Does this do it?
Back: Some Key Challenges