The Two (Computational) Faces of AI David Davenport Computer Engineering Dept., Bilkent University Ankara – TURKEY PT-AI talk Thessaloniki Oct. 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. PT-AI 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 PT-AI

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, … PT-AI

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! PT-AI

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. PT-AI

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, … PT-AI

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? PT-AI

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? PT-AI

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 PT-AI 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 PT-AI

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. PT-AI

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… PT-AI

Communication.... PT-AI

Storage... (copy) PT-AI

Recognition... (copy) PT-AI

Storage... (link) PT-AI

Recognition... (link) PT-AI exact/partial match - flat/hierarchical structure

Internal & External symbols... PT-AI C A T external symbols internal symbols

Relating word to object PT-AI audio senses visual senses “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 abduction fill-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) PT-AI 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. PT-AI

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)! PT-AI

The End (… of the beginning?) Thank you. PT-AI 2011