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== Deliverables ==

 * TBD

== List of available reference and or background materials ==
 * TBD
Video Tutorials
 * TBD
 * TBD

Not Released Yet!!! DBM130 - Designing Intelligence in Interaction




  • -none yet-

Learning objectives

The mission of the Industrial Design Department at Eindhoven University of Technology is to perform research on and provide education in: Creating intelligent systems, products and related services in a societal context. Industrial Design of the future is very much the design of intelligent products. In this course we introduce several perspectives into the keyword “intelligence”.

Learning activities

  • Intelligence for optimization. There exists algorithms for solving a class of problems called "combinatorial optimization". Typical examples are finding the shortest path in a network (packet routing), finding a tour along cities (delivery service) or finding an optimal path along graph edges (3D printing). Loe Feijs will illustrate the famous traveling salesman problem showing an interactive and intelligent G-code generator project for shoe soles (joint work with Troy Nachtigall). Another illustration is the optimal computerized embroidery path for the Pied de Pulse project (joint work with Marina Toeters).
  • Information processing for learning systems: A concept of information processing is presented that proposes an inverted U-shaped function between incongruity and information. This concept leads to important design recommendations for interactive systems with learning (Matthias Rauterberg).
  • Pattern recognition and neural network: we introduce and explain the basic concepts of pattern recognition and neural networks by showing a concrete example of image recognition, and discuss how these techniques can be applied in designing interactive products and systems (Jun Hu).
  • Design of social scenarios (provides methods for creation of social scenarios like ANT and AT (activity theory) (Emilia Barakova).
  • Adaptivity in games - how to optimally engage the cognitive system: Games revolve around learning in an engaging manner, but what might be boring for one person may be too challenging for another. This lecture details a variety of intelligent mechanisms and user interfaces to optimally engage the cognitive system of the player, and to keep the user in a flow state (Erik van der Spek).
  • Supporting the design of intelligent systems with OOCSI: how to design a system with bottom-up intelligence and constraints on information sharing, while making use of connection semantics, self-organization and Adaptivity (Mathias Funk).
  • Control systems, dynamic systems, and Blocks World, AI for robot programming. The blocks world is one of the most famous planning domains in artificial intelligence (Frank Delbressine).
  • Simulating behavior: Systems and services showing adaptive or emergent behavior, either triggered by the environment or by themselves, are often experienced as being intelligent. We will discuss modeling of complex systems, emergent behavior, and simulations of these behaviors (Peter Peters).

Information about lecturers

  • prof.dr.ir. Loe Feijs (l.m.g.feijs@tue.nl). He has a background in computer science and interaction design.

  • prof.dr. Matthias Rauterberg (g.w.m.rauterberg@tue.nl). He has a background in computer science and psychology.

  • dr.ir. Emilia Barakova (e.i.barakova@tue.nl). She has a background in computer science.

  • dr.ir. Frank Delbressine (f.l.m.delbressine@tue.nl). He has a background in mechanical engineering.

  • dr. Mathias Funk (m.funk@tue.nl). He has a background in computer science.

  • dr.PDEng.MEng. Jun Hu (j.hu@tue.nl). He has a background in computer science and interaction design.

  • dr.ir. Peter Peters (p.j.f.peters@tue.nl). He has a background in computer science and electronics.

  • dr. E.D. van der Spek (e.d.v.d.spek@tue.nl). He has a background in computer science and game design.

s4ph: AssignmentDescription (last edited 2016-11-29 11:54:36 by PeterPeters)