Snapshots of AI methods and applications

A. Aamodt, NTNU-IDI

Snapshots ofAI methods and applications

Agnar Aamodt and Keith Downing

Institutt for datateknikk og informasjonsvitenskap Seksjon for Intelligente Systemer

NTNU

A. Aamodt, NTNU-IDI

Hva er “Kunstig intelligens” – 1

“AI = Things that make you go WOW!” eller…??

vel, mer edruelig - om enn litt kjedeligere - så er kjerneideen:

“AI = Representation + Search” •The concept of search plays an important role in science and engineering• In one way, any problem whatsoever can be seen as a search for “the right answer”

A. Aamodt, NTNU-IDI

Software:• Pro-aktive beslutningsstøtte-

systemer• Automatisk data-analyse• Lærende systemer, f.eks.:

– Anbefalingssystemer– AI i spill– Ansiktsgjenkjenning

• Naturlig språk • Robotnavigering, syn, planlegging• Adapterende GUI• ...

Embedded systems– Intelligente komponenter i totalsystemer (hardware + software)

Annen hardware:– Autonome roboter

• Online bildefortolking• Samarbeid• Planleggingssystemer• …

Hjernesimulering• Kognisjonsvitenskap• Selvorganiserende systemer• …

Example applications

A. Aamodt, NTNU-IDI

har teknologiskperspektiv

har metoder

STUDIET AV INTELLIGENTE SYSTEMER

RELATERT TIL KOMPUTASJONELLE

PROSESSER

REALISERING AV DATASYSTEMER SOM KAN

SIES Å OPPVISE INTELLIGENT ADFERD

- DVS . ' SMARTERE ' SYSTEMER

SYMBOLORIENTERTE(KUNNSKAPSBASERTE METODER)

METODER

SUBSYMBOLSKE(BIO-INSPIRERTE METODER)

METODERKOGNITIV PSYKOLOGI

FILOSOFI

bygger bl.a. på

MATEMATIKK

BIOLOGI

KUNSTIG INTELLIGENS (AI)

harvitenskapeligperspektiv

er koblet via empirisk vitenskapelig metode

INFORMATIKK

er delfelt av

Hva er “Kunstig intelligens” – 2

har metoder

A. Aamodt, NTNU-IDI

KUNNSKAPSBASERTE METODER- UTVIKLINGSTRENDER

Heuristiskeregler

Regelbaserte systemer (f.eks.: MYCIN)

A. Aamodt, NTNU-IDI

Kontroll-kunnskap

Heuristiskeregler


Eksplisitt kontrollkunnskap (f.eks. NEOMYCIN) - kunnskap om typer regler for typer tilstander

A. Aamodt, NTNU-IDI

Kontroll-kunnskap

Heuristiskeregler


Dypere modeller, lærebok-kunnskap (f.eks. CASNET) - flere relasjoner, semantiske nett, rammer

Dypkunnskap

A. Aamodt, NTNU-IDI

Kontroll-kunnskap

Heuristiskeregler

Spesifikke case

Dyp kunnskap


Fra generell kunnskap til situasjons-spesifikke case(f.eks. CYRUS, PROTOS) - case-basert resonnering

A. Aamodt, NTNU-IDI

The Case-Based Reasoning (CBR) Cycle

(Aamodt&Plaza 1994)

A. Aamodt, NTNU-IDI

Kontroll-kunnskap

Heuristiskeregler

Spesifikke case

Dyp kunnskap


Integrerte systemer (f.eks. SOAR, CREEK, META-AQUA) - totalarkitekturer for intelligent problemløsning

A. Aamodt, NTNU-IDI

VIDEO CLIPHerb Simon

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A. Aamodt, NTNU-IDI

VIDEO CLIP

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A. Aamodt, NTNU-IDI

Subsymbolic / Bio-inspired AI Methods

A. Aamodt, NTNU-IDI

Emergence

• The signal feature of life is not the carbon-based substrate...(but)...that the local dynamics of a set of interacting entities (e.g. molecules, cells, etc.) supports an emergent set of global dynamical structures which stabilize themselves by setting the boundary conditions within which the local dynamics operates (Charles Taylor, biologist, UCLA)

A. Aamodt, NTNU-IDI

Swarm Intelligence

€

e = mc 2

222 yxz +=

• Follow Trail• Find Food•Make Trail

A. Aamodt, NTNU-IDI

Termite Arch-Building (Stigmergy)

pheremone

Turtles, Termites and Traffic Jams: Explorationsin Massively Parallel Microworlds (Resnick, 1994)

A. Aamodt, NTNU-IDI

Columns to Arches

Positive Feedback:Pheromone Concentration

in middle gets higher and higheras more dirt balls are added.

A. Aamodt, NTNU-IDI

Boids (Craig Reynolds)

http://www.red3d.com/cwr/boids/

A. Aamodt, NTNU-IDI

Ubiquity of Emergence

A. Aamodt, NTNU-IDI

Emergence & Intelligence

Emergence Spectrum

How does intelligent behavior arise from the interactions of 100 billion neurons, without central control?

How has the brain evolved?

A. Aamodt, NTNU-IDI

Evolutionary Progressions along the Intelligence Spectrum

Living organisms ComputersSense & Act: 10,000,000+ years. 15+ yearsReason: 100,000+ years. 30+ yearsCalculate: 1,000+ years 50+ years

• Evolution of reasoning was tightly constrained and influenced by sensorimotor capabilities. Else extinction!

• GOFAI systems are often in their own little worlds, making unreasonable assumptions about independent sensorimotor apparatus.

• To achieve AI’s scientific goal of understanding human intelligence, the road from sense-and-act to reasoning via simulated evolution may be the only way.

A. Aamodt, NTNU-IDI

Cognitive Incrementalism• Tacit assumption of SEAI research.

• Cognition (and hence common sense) is an extension of sensorimotor behavior.

• This is the idea that you do indeed get full-blown, human cognition by gradually adding ’bells and whistles’ to basic (embodied, embedded) strategies of relating to the present at hand…Mindware, pg. 135 (Andy Clark, 2001).

• I am, therefore I think.

• Brooks, Steels, Pfeifer, Scheier, Beer, Thelens, Nolfi, Floreano…

A. Aamodt, NTNU-IDI

Darwinian Evolution

Genotypes

Phenotypes

Morphogenesis

Natural Selection

Recombination & Mutation

Ptypes

Gtypes

ReproductionSex

Genetic

Physiological, Behavioral

A. Aamodt, NTNU-IDI

Evolutionary Algorithms

Bit Strings

Parameters, Code,

Neural Nets,Rules

Translate

Performance Test

Recombination & Mutation

P,C,N,R

Bits

Generate

Semantic

Syntactic

R &M

A. Aamodt, NTNU-IDI

Artificial Neural Networks

A. Aamodt, NTNU-IDI

WorldModel Behav

GenBody World

Brain

GOFAI

WorldModel

BehavGen Body

World

Brain

SEAI

The world is its own best model… Rodney Brooks

WorldModel

BehavGen Body World

Connectionism

A. Aamodt, NTNU-IDI

GOFAI -vs- SEAI Brittle Nerds -vs- Well-Rounded Insects

Knowledge

Selection Pressure

Knowledge Cramming -vs-

Adaptive Systems

GOFAI

SEAI

A. Aamodt, NTNU-IDI

A master thesis in AI at IDI– a few examples

A. Aamodt, NTNU-IDI

IDIs Seksjon for Intelligente Systemer - Organisering i 3 faggrupper

• Kunnskapsbaserte systemer – Case-basert resonnering– Kunnskapsmodellering– Intelligente agenter– Adaptive brukergrensesnitt– Usikkerhetsbehandling/grafiske

modeller– Bildebehandling/kunstig syn– Maskinlæring/datamining.

• Selvorganiserende systemer– Evolusjonære metoder– Konneksjonisme– Nevrovitenskap– Kunstig liv– Maskinlæring

• Språkteknologi – Naturlig språklig fortåelse– Beregnbar logikk– Tekstmining– BusTuc

• 31 ansatte:– 11 heltidsstillinger– 4 Deltid– 3 Forskere– 13 PhD studenter

• 20 – 25 MSc studenter per år

A. Aamodt, NTNU-IDI

Improved game AI through case-based and statistical reasoning

Eksempler på master-oppgaver

A. Aamodt, NTNU-IDI


A. Aamodt, NTNU-IDI


A. Aamodt, NTNU-IDI

Bilde- og/eller Video-analyse (Her: Segmentere bilder av karbonfiberarmert epoxy)


A. Aamodt, NTNU-IDI

Bilde- og/eller Video-analyse (Her: Segmentere bilder av fisk i Mauritius)


A. Aamodt, NTNU-IDI

Robots (pictured) that interact with either a real or simulated other robot. Within our PUCKER system, researchers and students can easily test their AI control strategies on this type of robot (e-pucks).


A. Aamodt, NTNU-IDI

Intelligent Hardware

Today’s hardware technologies, especially Field programmable Gate Arrays (FPGAs), provide many possibilities for the creation of intelligent Hardware - that is AI techniques embedded in hardware.

Such embedding may be for the purpose of speed-up of a given AI

technique for perhaps real-time application requirements or for the purpose of creating hardware circuits, applying bio-inspired techniques as the design technique.

The latter is known as the field of Evolvable Hardware and

includes applications in today’s technology and approaches to achieve computation in tomorrow’s technology. Application areas range from Vision, art to electronic circuits.


A. Aamodt, NTNU-IDI


Språkteknologi - maskinoversetting

A. Aamodt, NTNU-IDI


A. Aamodt, NTNU-IDI

Discovery of causal relations in incident reports

• An incident report (i.e., a 'textual case') describes how a problem unfolds. That is, the story starts with less important 'symptoms'/evidence which, in turn, triggers/causes more serious ones, and this chain of evidence ends up with an undesired, anomalous event. It is important to identify the events when they are small, and discover the causal mechanisms underlying the chain of events.

• Use of eye-tracking in the selection of important features in a text and determining how important they are - the latter is called 'weighting’. This in cooperation with people at Dragvoll.


Textual CBR.

A. Aamodt, NTNU-IDI

Computer Assisted Assessmentand Treatment of Pain

Probabilistic networks, Rules, CBR, meta-level reasoning


A. Aamodt, NTNU-IDI

Data mining and Decision support in Fish Farming


A. Aamodt, NTNU-IDI

Evolving Populations ofSocial Insects to Perform

Annular Sorting

P = Pick up D = DepositF = Forward B = BackwardL = Left R = Right

Sensing

Acting

Vegard Hartmann Andre Hei Vik


A. Aamodt, NTNU-IDI

Fitness Evaluation


A. Aamodt, NTNU-IDI

Three-object annular structure


A. Aamodt, NTNU-IDI

• One day of unwanted downtime on this rig means increased cost of 1,6 MNOK for the ongoing drilling operation.

• Providing the relevant experience and getting the right information precisely when needed will reduce unwanted operational downtime.

• The result is a more reliable drilling process, reduced drilling costs, and increased productivity.

Reducing unwanted downtime in oil drilling


A. Aamodt, NTNU-IDI

Improved decision support through experience capture and reuse - pattern analysis - case-based reasoning


A. Aamodt, NTNU-IDI

VIDEO CLIPEksempler på master-oppgaver

A. Aamodt, NTNU-IDI

DIS har deltatt i etablering av tre spin-off selskaper:

- LingIT AS - naturlig språk tolkning og dialogsystemer

- Trollhetta AS - bildeanalyse og beslutningsstøtte

- Verdande Technology AS - erfarings-lagring og aktiv gjenbruk, primært innen oljeboring

A. Aamodt, NTNU-IDI

AI - covers a lot of methods and application areas- is interesting, useful, and fun

So, learn your- basic AI formalisms, such as - logics

- representations - state-space search methods

Link to videos shown (and more!): http://videolectures.net/aaai07/http://videolectures.net/aaai08/http://videolectures.net/ijcai09_video_competition/

A useful link to all of AI: http://www.aaai.org/aitopics

A. Aamodt, NTNU-IDI

A. Aamodt, NTNU-IDI

Evolutionary Computation

Documents

Snapshots of AI methods and applications