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Snapshots of AI 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 Example applications Software: • Pro-aktive beslutningsstøttesystemer • Automatisk data-analyse • Lærende systemer, f.eks.: – Anbefalingssystemer – AI i spill – Ansiktsgjenkjenning • Naturlig språk • Robotnavigering, syn, planlegging • Adapterende GUI • ... A. Aamodt, NTNU-IDI Embedded systems – Intelligente komponenter i totalsystemer (hardware + software) Annen hardware: – Autonome roboter • Online bildefortolking • Samarbeid • Planleggingssystemer • … Hjernesimulering • Kognisjonsvitenskap • Selvorganiserende systemer • … Hva er “Kunstig intelligens” – 2 INFORMATIKK STUDIET AV INTELLIGENTE RELATERT REALISERING AV DATASYSTEMER SOM KAN SYSTEMER TIL KOMPUTASJONELLE SIES Å OPPVISE INTELLIGENT ADFERD - DVS . ' SMARTERE ' SYSTEMER er delfelt av PROSESSER er koblet via empirisk vitenskapelig metode har vitenskapelig perspektiv har teknologisk perspektiv KUNSTIG INTELLIGENS (AI) bygger bl.a. på har metoder har metoder MATEMATIKK SYMBOLORIENTERTE METODER (KUNNSKAPSBASERTE METODER) FILOSOFI KOGNITIV PSYKOLOGI BIOLOGI A. Aamodt, NTNU-IDI SUBSYMBOLSKE METODER (BIO-INSPIRERTE METODER) KUNNSKAPSBASERTE METODER - UTVIKLINGSTRENDER Heuristiske regler Regelbaserte systemer A. Aamodt, NTNU-IDI (f.eks.: MYCIN) KUNNSKAPSBASERTE METODER - UTVIKLINGSTRENDER Kontroll-kunnskap Heuristiske regler A. Aamodt, NTNU-IDI Eksplisitt kontrollkunnskap (f.eks. NEOMYCIN) - kunnskap om typer regler for typer tilstander KUNNSKAPSBASERTE METODER - UTVIKLINGSTRENDER Kontroll-kunnskap Heuristiske regler Dyp kunnskap A. Aamodt, NTNU-IDI Dypere modeller, lærebok-kunnskap (f.eks. CASNET) - flere relasjoner, semantiske nett, rammer KUNNSKAPSBASERTE METODER - UTVIKLINGSTRENDER Kontroll-kunnskap Heuristiske regler 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 KUNNSKAPSBASERTE METODER - UTVIKLINGSTRENDER Kontroll-kunnskap Heuristiske regler Spesifikke case Dyp kunnskap Integrerte systemer (f.eks. SOAR, CREEK, META-AQUA) - totalarkitekturer for intelligent problemløsning A. Aamodt, NTNU-IDI Herb Simon A. Aamodt, NTNU-IDI A. Aamodt, NTNU-IDI A. Aamodt, NTNU-IDI 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 z 2 x2 y 2 • Follow Trail • Find Food •Make Trail A. Aamodt, NTNU-IDI Termite Arch-Building (Stigmergy) Turtles, Termites and Traffic Jams: Explorations in Massively Parallel Microworlds (Resnick, 1994) pheremone A. Aamodt, NTNU-IDI Columns to Arches Positive Feedback: Pheromone Concentration in middle gets higher and higher as 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 Sense & Act: Reason: Calculate: Living organisms Computers 10,000,000+ years. 15+ years 100,000+ years. 30+ years 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 Physiological, Behavioral Phenotypes Natural Selection Ptypes Reproduction Sex Morphogenesis Genotypes Recombination & Mutation Genetic A. Aamodt, NTNU-IDI Gtypes Evolutionary Algorithms Parameters, Code, Neural Nets, Rules Semantic Performance Test P,C,N,R R &M Translate Generate Bit Strings Syntactic A. Aamodt, NTNU-IDI Recombination & Mutation Bits Artificial Neural Networks A. Aamodt, NTNU-IDI GOFAI World Model Behav Gen World Body Brain Connectionism World Model Behav Gen World Body SEAI The world is its own best model… Rodney Brooks World Model Behav Gen Brain A. Aamodt, NTNU-IDI Body World GOFAI -vs- SEAI Brittle Nerds -vs- Well-Rounded Insects Selection Pressure Knowledge GOFAI SEAI Knowledge Cramming -vsAdaptive Systems 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 – – – – – A. Aamodt, NTNU-IDI 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 Eksempler på master-oppgaver Improved game AI through case-based and statistical reasoning A. Aamodt, NTNU-IDI Eksempler på master-oppgaver A. Aamodt, NTNU-IDI Eksempler på master-oppgaver A. Aamodt, NTNU-IDI Eksempler på master-oppgaver Bilde- og/eller Video-analyse (Her: Segmentere bilder av karbonfiberarmert epoxy) A. Aamodt, NTNU-IDI Eksempler på master-oppgaver Bilde- og/eller Video-analyse (Her: Segmentere bilder av fisk i Mauritius) A. Aamodt, NTNU-IDI Eksempler på master-oppgaver 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 (epucks). A. Aamodt, NTNU-IDI Eksempler på master-oppgaver 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 bioinspired 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 Eksempler på master-oppgaver Språkteknologi - maskinoversetting A. Aamodt, NTNU-IDI Eksempler på master-oppgaver A. Aamodt, NTNU-IDI Eksempler på master-oppgaver Textual CBR. 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. A. Aamodt, NTNU-IDI Eksempler på master-oppgaver Computer Assisted Assessment and Treatment of Pain Probabilistic networks, Rules, CBR, meta-level reasoning A. Aamodt, NTNU-IDI Eksempler på master-oppgaver Data mining and Decision support in Fish Farming A. Aamodt, NTNU-IDI Eksempler på master-oppgaver Evolving Populations of Social Insects to Perform Annular Sorting Vegard Hartmann Acting Sensing A. Aamodt, NTNU-IDI P = Pick up F = Forward L = Left D = Deposit B = Backward R = Right Andre Hei Vik Eksempler på master-oppgaver Fitness Evaluation A. Aamodt, NTNU-IDI Eksempler på master-oppgaver Three-object annular structure A. Aamodt, NTNU-IDI Eksempler på master-oppgaver Reducing unwanted downtime in oil drilling • 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. A. Aamodt, NTNU-IDI Eksempler på master-oppgaver Improved decision support through experience capture and reuse - pattern analysis - case-based reasoning A. Aamodt, NTNU-IDI Eksempler 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 A. Aamodt, NTNU-IDI