Artificial Intelligence Master at UPC: some experience on applying AI to real world problems

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Artificial Intelligence solutions forArtificial Intelligence solutions for real world problems real world problems

Departament de Llenguatges i Sistemes Informàtics (UPC)Departament de Llenguatges i Sistemes Informàtics (UPC)

26/05/201026/05/2010

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ContentsContents

What is Artificial Intelligence useful for?

Some examples of using AI

AI and Medicine

AI in Industrial Processes

AI for on-line, real-time Text Translation

AI for flexible, adaptive on-line systems

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What is Artificial Intelligent useful for?What is Artificial Intelligent useful for?

To create computational systems with some human-like capabilities.

ReasoningReasoning

ClassificationClassification

Decision makingDecision making

Learning/adaptationLearning/adaptation

Human communicationHuman communication

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What is Artificial Intelligent useful for?What is Artificial Intelligent useful for?

Classical applications include:

Decision support systems / Expert SystemsDecision support systems / Expert Systems Data MiningData Mining Natural Language ProcessingNatural Language Processing RoboticsRobotics

… But there are lots of new applications coming from latest technologies! (in special Internet):

Automatic user profilingAutomatic user profiling Recommender systemsRecommender systems Social networkingSocial networking e-Commercee-Commerce Future Internet, Internet of Things, Cloud Computing…Future Internet, Internet of Things, Cloud Computing…

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Some examples of using AISome examples of using AI

The following are just some examples of our own experience in the use of AI to solve real problems.

Hotels

Museums

Restaurants

Map generator

Weather

Public Transport

CinemasLegal body

policies

Inte

rfa

ce

Recommendation System

Social modeler

System

User modeler

feedback

feedback

feed

feed

Route planner Booking/payment

Traffic

The Webcontent

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AI and MedicineAI and Medicine

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AI to assist patients’ autonomyAI to assist patients’ autonomy

The problem: European population is becoming older Danger of unsustainable healthcare Need to find technologies that will assist

elders in their daily life, incresing theirautonomy

Idea: Development of intelligent, semi-autonomousintelligent, semi-autonomous

assistive devices assistive devices for persons with disabilities(both cognitive and/or motor).

• These persons will reach a sufficient degree of autonomy with a high level of safety and comfort.

Approach: Robotics, Agent-oriented technologies, Robotics, Agent-oriented technologies,

Ambient Intelligence, User ProfilingAmbient Intelligence, User Profiling.

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Ambient Intelligence


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Multiagent Systems

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step 3

INPUT:

real time forces anduser relative position

Real Time Simulation

Application:

Design and verification of strategiesfor user intent detection

OUTPUT

Enviroment motionrelative to IW

Relevant datavisual feedback

sensor information

INPUT: path and timing Direct Model

Application:

Design of motor torques strategies

step 1

OUTPUT:

forcesand torques

step 2

INPUT:

programmedforces anduser relativeposition

Inverse Model

Application:

Verification of motor torques strategies

OUTPUT: path and timing

sensor information

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AI to assist patients’ autonomyAI to assist patients’ autonomyWho shall I contact to know more?Who shall I contact to know more?

Ulises Cortés Cristian Barrue Guiem Bosch

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AI for Brain Tumor DiagnosisAI for Brain Tumor Diagnosis

The problem: Brain tumour diagnosis is a sensitive and

complex task usually left to specialized radiologists (IDI).

Due to the anatomical constraints of these pathologies, experts’ decision making often relies upon information acquired through non-invasive measurement methods.

• MRI (neuroimaging) The interpretability of the results is

paramount in brain tumour diagnosis. Idea:

Machines learn to better recognise tumors through recognise tumors through MRS MRS (neurospectra), and help doctors in diagnosis

Approach: Data Mining and rule extraction techniquesData Mining and rule extraction techniques

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12/04/23 [email protected] 13

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AI for Brain Tumor DiagnosisAI for Brain Tumor Diagnosis

Rule extraction from raw data

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AI for Brain Tumor DiagnosisAI for Brain Tumor DiagnosisWho shall I contact to know more?Who shall I contact to know more?

Alfredo Vellido Angela Nebot Rene Alquezar

INTERPRET INTERPRET ToolTool

INTERPRET INTERPRET ToolTool

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AI in Industrial ProcessesAI in Industrial Processes

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AI for textile machinery AI for textile machinery configurationconfiguration

The Problem: European textile industries need to

innovate to compete with other countries and open to new markets

Innovate means create new fabrics• Mix different materials• Mix them in different, unprecedented ways

A critical step is the textile machine setup• Manual set-up can take weeks of trial and error• It can also be costly in terms of raw materials

Idea: A systems that allows the machines to auto-configure machines to auto-configure

themselvesthemselves when presented with a description of the target fabric

Approach: Use Case-Based ReasoningCase-Based Reasoning.

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Raw materials parameters Machinery settings parameters End product parameters

RP1 RP2 RP3? RP4 RP5?

RP1 RP2 RP3 RP4 RP5

MP1? MP2 MP3 MP4 MP5

MP1 MP2 MP3 MP4 MP5

EP1 EP2? EP3 EP4 EP5?

EP1 EP2 EP3 EP4 EP5

CBR System

Diam

eter

Fiber Fib

er

dens

ity

Cyl

inde

r sp

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twis

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Porosity

Predicted value

Requiredvalue

To make easier the production of new advanced textile products Prediction of the required unknown parameters To reduce the economical cost and time required for thetextile machinery set-up Doing less tests in the textile machines

Case-Based Reasoning: Using previous process experiential knowledge

AI for textile machinery configurationAI for textile machinery configuration

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AI for textile machinery configurationAI for textile machinery configurationWho shall I contact to know more?Who shall I contact to know more?

Miquel Sànchez-Marré Beatriz Sevilla

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AI for on-line, real-time Text TranslationAI for on-line, real-time Text Translation

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The Problem: EU is a union of states

with several languagesused

Continuous need of translations from one tothe other.

Idea: to develop a set of tools tools

for translating texts for translating texts between multiple languages in real time with high quality.

Approach: Use multilingual grammars based on semantic interlinguasmultilingual grammars based on semantic interlinguas.

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Necesito que me pases los resultados

Ik begrijp je niks!

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AI for on-line, real-time Text TranslationAI for on-line, real-time Text TranslationWho shall I contact to know more?Who shall I contact to know more?

Lluís Màrquez David Farwell Cristina España Horacio Rodríguez Xavier Carreras Lluís Padró

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AI for flexible, adaptive on-line systemsAI for flexible, adaptive on-line systems

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AI for flexible, adaptive on-line systemsAI for flexible, adaptive on-line systems Problem:

New generations of networked service applications should be able to:

• communicate and reconfigure at runtime• adapt to their environment• dynamically combine sets of building

block services into new applications

Idea: The mechanismsmechanisms used today to organise

the vastly complex interdependencies found in human, social, economic in human, social, economic behaviour behaviour will be essential to structuring to structuring future distributed software systems distributed software systems

Approach: To bring together Agent TechnologyAgent Technology, Organizational Organizational

TheoryTheory and new technologies on Model Driven design Model Driven design to create a framework for software and services engineering

Hotels

Museums

Restaurants

Map generator

Weather

Public Transport

CinemasLegal body

policies

Inte

rfa

ce

Recommendation System

Social modeler

System

User modeler

feedback

feedback

feed

feed

Route planner Booking/payment

Traffic

The Webcontent

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Methodology

Fram

ework

Coordination level:- coordination patterns- task allocation- actor expectation

Organizational level:- norms and regulations- organizational structure- communication ontology- evaluation indicators

WSWS

WS

WS

WSnewWS

Existing platformsExisting servicesNew servicesService interactions

SDSD

SD

SD

SD SD

Service level:- semantic service description (SD)- standards specification

actor

actor

actor

actor

role

dynamic assignment

Functional instantiation

role role role

actual deployment

WHY?(motivations)

WHAT?(possible actions, plans)

HOW?(available services)

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AI for flexible, adaptive on-line systemsAI for flexible, adaptive on-line systems

A set of services is selected to fulfill a user request.

The service selected for the “find museum info” task fails …

No alternate service isfound for the task re-plan

A new set of services is invoked and the results merged to fulfill the user request.

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AI for flexible, adaptive on-line systemsAI for flexible, adaptive on-line systemsWho shall I contact to know more?Who shall I contact to know more?

Javier Vázquez Sergio Álvarez Roberto Confalonieri Sofia Panagiotidi Juan Carlos Nieves Ignasi Gómez

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Some collaborationsSome collaborations

3scale Networks S.L. Sisltech TMT Telecom Factory Techideas Qporama ASCAMM ISOCO Servei Català de la Salut Agencia Catalana de l’Aigua Ajuntament de Barcelona Institut Guttmann Organització Mundial de la Salut Telefònica I+D IBM Labs UK. Fujitsu Gmbh


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ConclussionsConclussions

AI allows to create smarter, more flexible computational systems that can:

Help humans in cognitive tasksHelp humans in cognitive tasks Adapt to human needsAdapt to human needs Communicate with humansCommunicate with humans Dynamically adapt to changesDynamically adapt to changes

There are several application areas when AI is key.

The Future Internet is one of them!The Future Internet is one of them!
