Is it Possible to BuildDramatically Compelling Interactive

Digital Entertainment? v2Selmer 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

Games?

Is it Possible to BuildDramatically 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 BuildDramatically 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

TheorySemantics Metatheory

LPC

Propositional Calculus

p, q, r, … and truth-functional connectives

Easy Fitch-style and natural deduction, resolution, etc.

Truth tables! Sound, complete, compact, decidable

LI

First-Order Logic

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

Unfortunately…Name Alphabet Grammar Proof

TheorySemantics Metatheory

LPC

Propositional Calculus

p, q, r, … and truth-functional connectives

Easy Fitch-style and natural deduction, resolution, etc.

Truth tables! Sound, complete, compact, decidable

LI

First-Order Logic

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

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 actioninputs: p, a perceptstatic: 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 + 1return action

The Wumpus World

We Build Agents Like This in the Minds & Machines Laboratory

But Personhood Involves…

• Ability to communicate in a language

• Autonomy (“free will”)

• Creativity

• Phenomenal consciousness (= subjective awareness, qualia, what-it’s-like-to-be-you consciousness, P-consciousness)

• Robust abstract reasoning

today

Turing Test

Judge What color and in whatstyle is your hair?

Judge

What color and in whatstyle is your hair? Designer

In the TT, it’s Really Judge vs. Designer

I can handle tha- uh, itcan handle that one.

Judge (= Designer)Designer (= Judge)

The Lovelace Test

o

S

How did it do that?

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

Percepts: ? Actions:Design remaining letters

A B C D E F … Z

Letter Spirit System as anIntelligent Agent

Percepts:seed letters

Actions:Design remaining letters

A B C

Letter Spirit

D E F … Z

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 Me1 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 indicatesthat for this dream to become

reality will require somepreternaturally 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