I&D como base para a Inovação

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Timothy Dwight Powell
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1 I&D como base para a Inovação R&D as the basis for Innovation Rosaldo Rossetti Laboratório de Inteligência Artificial e Ciência de Computadores, LIACC Departamento de Engenharia Informática, DEI-FEUP rossetti@fe.up.pt 1

2 LIACC LIACC is an R&D Unit of Universidade do Porto Faculdade de Engenharia, DEI Faculdade de Ciências, DCC Other members from Universidade do Minho Politécnico do Porto Politécnico de Bragança Politécnico de Viana do Castelo Politécnico do Cávado e Ave 2

3 LIACC-FEUP DAI & Multi-agent Systems Intelligent Systems Interoperability for services networking and cooperation Planning, Scheduling and Disruption Management Agents: Adaptation, Learning and Emotions Argumentation-based Agents Text Mining and Social Network Analysis Cloud, Parallel computing Multi-Agent Systems Infrastructures and Applications Simulation & Robotics Theories and methodologies of modelling and simulation Social Simulation and analysis of complex systems Socio-technical systems engineering and analysis Intelligent Transportation Systems Smart Cities Interactive and Social Robotics Computer Vision Spatio-temporal data analysis Behaviour modelling techniques Artificial Intelligence and Games 3

4 Agenda Research Innovation Timeline for R&D&I LIACC & ARMIS Collaboration Challenge LIACC s R&D Collaborations 4

5 Research Research by definition is a creative activity to produce knowledge. Dimension Basic Research Applied Research Type of knowledge produced Scientific Discovery (Science) Technological Application (Technology) Motivation Intellectual curiosity Solving problems Key questions Is it true? Does it work? Objective To understand phenomena To come up with solutions 5

6 Research Basic Research Science Applied Research Technology The classical view for the Basic Research & Applied Research relationship 6

7 Innovation : the introduction of something new : a new idea, method, or device Merriam-Webster, Dic. : the action or process of innovating : make changes in something established, especially by introducing new methods, ideas, or products Oxford, Dic. 7

8 Innovation old-fashioned Market Society Innovation Technology Basic Research Science Applied Research Stakeholders in the co-creative innovation process (Eriksson, et al. 2005) 8

9 Timeline for R&D&I long-term mid-term short-term Science Basic Research Technology Applied Research Innovation 9

10 Driverless Car of the Future, advertisement for America s Electric Light and Power Companies, 1950s 10

11 GM & Radio Corporation of America (RCA), 1950s 11

12 Ernst Dickmanns VaMoRs Mercedes van, Bundeswehr University Munich,

13 Ernst Dickmanns VaMoRs Mercedes van, Bundeswehr University Munich,

14 DARPA Grand Challenge, 2005 Winner Stanley (L), runner-ups Sandstorm(R) and H1ghlander (middle) 14

15 Daimler Autonomous long-distance drive in rural and urban traffic Mercedes-Benz S-Class INTELLIGENT DRIVE,

16 Towards a co-creative innovation platform LIACC-ARMIS R&D&I COLLABORATION 16

17 Artificial Transportation Systems With the ability to integrate different transportation models and solutions in a virtual environment, ATS serve as an aid to support decision-making and provide a natural ground where new approaches can be experimented with while avoiding the natural drawbacks of dealing directly with real critical domains, such as ITS. F.-Y. Wang (2003) IEEE ITSC 17

18 Artificial Transportation Systems An extension of computer simulation for system analysis and decision support of transportation systems. F.-Y. Wang (2005) IEEE ITSC Agent-based modelling and programming Large-scale distributed computer techniques Complex and interactive socio-technical systems Multi-disciplinary approaches Novel solutions and perspectives 18

19 Artificial Transportation Systems 19

20 LIACC s ATS: MAS-Ter Lab off-line decision support models optimisation strategies inductor on-line actuation models real world/living labs 2005 expert (real/artificial) agents EA EA EA CA EA EA EA P1, P2, P3,..., Pn (control policies) ITS ITS ITS observes, analyses and suggests alternatives ITS artificial transportation domain TA UA UA replication TA TA TA UA UA replication mixed realities 20

21 LIACC s ATS: MAS-Ter Lab Regulator Operator App Provider User Applications Services APIs & Open Data Integration/Interoperation Representation Multiple Resources 21

22 Rossetti & Liu (2015) Presents a collection of different pieces of work supporting the concept and implementation of Artificial Transportation Systems! It features contributions from: ATSS Workshops ATSS Special Sessions At IEEE ITS Conferences 22

23 Real-world domain regulator / operator / app provider / user LIACC s ATS: MAS-Ter Lab expert (real / artificial) agents Advisor Auditor Monitor Predictor Planner Tutor artificial domain - representation integration layer Model Driven Data Driven 23

24 ARMIS NEXT 24

25 ARMIS NEXT 25

26 ARMIS NEXT 26

27 Computer Vision & ITS 27

28 Computer Vision & ITS 28

29 29

30 Social Media and Networks: Sharing opinions, sentiments, preferences, and information 30

31 Crowdsensing & ITS 31

32 Travel-related tweets in the city of Rio de Janeiro 32

33 Travel-related tweets in the city of São Paulo 33

34 Travel-related tweets in the city of New York 34

35 Challenge How to effectively integrate citizens in the co-creative innovation of transportation systems towards smarter mobility solutions? 35

36 LIACC s R&D Collaborations 36

37 Obrigado! Rosaldo Rossetti Laboratório de Inteligência Artificial e Ciência de Computadores, LIACC Departamento de Engenharia Informática, DEI-FEUP rossetti@fe.up.pt 37

AGENTS AND AGREEMENT TECHNOLOGIES: THE NEXT GENERATION OF DISTRIBUTED SYSTEMS

AGENTS AND AGREEMENT TECHNOLOGIES: THE NEXT GENERATION OF DISTRIBUTED SYSTEMS Vicent J. Botti Navarro Grupo de Tecnología Informática- Inteligencia Artificial Departamento de Sistemas Informáticos y Computación