Intelligent Systems

This course is offered in the first semester of Academic Year 2003-2004 for the "Laurea Specialistica" (Master) in Computer Science.

Program (to be refined).

Computational Intelligence. Introduction. The biological, vision and motion perspective. The Turing machine. Machines and Mind. The Artificial life. Flocks and Avatars. Introduction to Artificial Intelligence. Fuzzy systems.

Biological Intelligence.
The neuron. Functional models. Geometrical models. The L-systems. Fractal models.
Neural Networks. The McCulloch-Pitts model. The perceptron. The theory of learning from experience. The delat rule. Hebbian learning.
Cerebral maps. Self-organizing maps. Clustering. Kohonen maps.
Radial Basis Function Neural Netoworks. Learning with RBF networks. Multi-scale approximation through RBF networks. Real-time issues.
Reinforcement learning. Classical conditioning. The credit-assignement problem. Learning with a Critic.
Cerebral networks. Networks for motion, vision, acting. Visuo-motor transformation.

Introduction to Virtual Reality
Introduction to Virtual Reality. Input systems. Graphical Engines. World generators. Output devices.

Visual Intelligence (Computer vision)

Artificial vision. Projective and perspective geometry. Calibration. 3D reconstruction.
Epipolar geometry. Structure from Motion. Structure from Features.
Reconstruction of 3D models from video.
Optical flow. Computation of 2D motion from optical flow. Features detection.
Structure from Motion. Reconstruction of a structure from translation. Instaneous epipole and its relationship with motion.

Specific issues
To be defined.

Motion Intelligence (Robotics).
Skeleton control.
Humanoid robotics.

A laboratory on robotics will be activated inside the FSE course. It will be given on saturday morning, in January 2004.