the two (computational) faces of ai david davenport computer engineering dept., bilkent university...
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The Two (Computational) Faces of AI
David DavenportComputer Engineering Dept.,Bilkent UniversityAnkara 06800 – TURKEY
Email: [email protected] talkThessalonikiOct. 2011
Explaining Cognition / AI•Scientific endeavor
& Engineering discipline“...an engineering discipline built
on an unfinished science”Matt Ginsberg, 1995
•Philosophers only complicated matters▫ confusing us about words
we thought we understood.
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•This is my naïve attempt to understand…
In the beginning…
•was the classical “symbolic” paradigm▫cognition seen as computation▫logical, rule-governed
manipulation of formal symbols… ▫but meaning & biological plausibility?
•enter the “connectionist” paradigm▫brain inspired, flexible, subsymbolic,
able to learn its own “symbols”, but opaque
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The Architecture of Cognition
•Is it symbolic & connectionist?▫Is one wrong?
Are they genuine alternatives? Or a hybrid of both? Or neither…
•Newer contenders:▫Dynamical systems, embodied, embedded,
radical embedded, situated, extended, interactivist, enactivist, …
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Engineering Cognition / AI
•Requirements: concerned with function, what is the problem that needs solving?
•Design: an abstract solution to problem.•Implementation: concrete, physical
mechanism corresponding to the design.•Test, distribution, maintenance
▫handled by environment & evolution!
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Functional Requirements
•Agents are small part of physical world▫so have limited knowledge & subject to
error•World has some regularities
“The unpredictability of the world makes intelligence necessary, the predictability makes it possible.”
•Agents make use of regularities▫detect, predict & select “best” action.
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Use Cases
•Example task types
1) Maintain body temperature, control engine speed, flower facing sun…
2) Track predator/prey even when occluded,walk/climb towards goal despite obstacles...
3) Converse in English, do math, tell fictional stories, socialise, …
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Different mechanisms…
•Example 1 type systems▫require only simple feedback control
•Example 3 type systems▫require… a full symbol system?
“A physical symbol system has the necessary and sufficient
means for [human-level] intelligent action.” Newell & Simon, 1976
•Note: PSS could do all types, but type 1 systems couldn’t ~~ c.f. newcomers?
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Design
•Constrained by functional requirements& by properties of available materials
•Claim designs will be computational•Take a broad view of computation
“computation as prediction/modeling”
why?
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Prediction / Modeling
•Target system & model•Map states & seq.
▫Find existing system▫Construct one anew ▫Use digital computer
•Rely on causation•Causal structure is all that matters
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Photo by Flickr user charamelody
Design (cont.)
•Constrained by functional requirements& by properties of available materials
•Claim designs will be computational•Take a broad view of computation
“computation as prediction/modeling”•Program/algorithm/computation is
“…an abstract specification for a causal system.”Chalmers, 1997
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Design for example type 1
•Type 1 (e.g. engine speed governor)▫only two actions (increase/decrease steam)▫predictable from current engine speed▫any mechanism that
provides such control is fine: Watt’s Centrifugal Governor (mechanical) Embedded microprocessor-based controller.
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Design for example type 3
•Type 3 ( human-level behaviour)▫with no a priori knowledge of world
an agent can only store what it senses& detect similar situations in the future.
▫combined with record of temporal sequence & of its actions
▫it has info to make “intelligent” actions!
But how? back to basics…
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Communication....
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Storage... (copy)
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Recognition... (copy)
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Storage... (link)
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Recognition... (link)
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- exact/partial match- flat/hierarchical structure
Internal & External symbols...
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C A Texternalsymbols
internalsymbols
Relating word to object
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audiosenses
visualsenses
“CAT”
Situation in which word “CAT” is heard and cat is seen
Logically•Conventional
“if a & b & c then z”
•Alternative, Inscriptors“if z then a & b & c”
▫causal, rule-following, “not”, but uses abductionfill-in expectations (top-down/bottom-up) so flexible
▫storing what seen, so syntax & semantics match▫decouple from input (state retaining)▫Model-like (simple incomplete or combine…~PSC)
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a b c
z
The Architecture of Cognition
•Is Cognition Symbolic or Connectionist?▫Differ based on “copy” or “link” storage▫Shown both can do the job, so▫they are genuine design alternatives.
(as are analog/digital & serial/parallel)•Is the PSSH wrong then?
▫No, it is setting functional requirements.
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To Conclude
•Presented a principled distinction between classical symbolic & connectionist approaches, showing them to be genuine design alternatives.
•Distinguished (Newell’s) PSS from the symbolic paradigm, per se.
•Hopefully in an understandable way(… so avoiding Bonini’s paradox)!
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The End
(… of the beginning?)
Thank you.
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