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The following are last minute news you should be aware of ;-)

 31/08/2017: Confirmed the date and room for the course presentations -> 14/09/2017 from 9:30 in V.S8-B
 25/07/2017: You can find here the grades of the 25/07/2017 call blank scores are for missing projects (which can count up to 7). 
 22/07/2017: You can find here the grades of the 04/07/2017 call blank scores are for missing projects (which can count up to 7). 
 06/07/2017: Added past exam text
 23/06/2017: Added slides on Convolution Aritmetics
 20/06/2017: Added all slides on Deep Learnig and updated Behavior-based slides with hybrid architectures
 12/06/2017: Added slides on Non verbal HRI, Feed Forward Neural Networks, and Deep learning
 11/04/2017: Added slides on Behavior Based Robotics
 11/04/2017: Added days for the lectures on Natural Language Processing
 31/03/2017: Added slides on PDDL
 31/03/2017: Swap of lectures between Bonarini and Matteucci on 19/5 and 26/5
 27/03/2017: Added slides on Planning
 19/03/2017: Added first classes pdf slides and some reference material (links and pdf)
 07/03/2017: Course starts today!

Contents

Course Aim & Organization

This course addresses the methodological aspects of Cognitive Robotics. Cognitive Robotics is about endowing robots and embodied agents with intelligent behaviour by designing and deploying a processing architecture making them apt to deliberate, learn, and reason about how to behave in response to complex goals in a complex world. Perception and action, and how to model them in neural and symbolic representations are therefore the core issues to address. Inspiring models of Cognitive Robotics arise from different disciplines: the neural architectures from neuroscience, the basic behaviours from ethology, motivations and emotions from psychology, the multirobot behaviour from sociology. Those models could be implemented in terms of formal logic, probabilistic, and neural models turning into embodied computational agents.


Teachers

The course is composed by a blending of theory and practice lectures from the course teacher and the teaching assistants (in order of appearance):


Course Program and Teaching Material

The course comprises theoretical lectures (30h regarding 1-3) and practical sessions (20h regarding 4-5):

  • Cognitive Robotics introduction
    • Cognition and the sense-plan-act architecture
    • Deliberative, reactive, and hybrid approaches
  • Deliberative systems for cognitive robots
    • Symbolic planning and PDDL
  • Bioinspired controllers for autonomous robots
    • Behavior based architectures
    • Neural networks and learning
  • Human-Robot interaction
    • Natural language processing
    • Non verbal human robot interaction
    • (Deep) learning for vision/nlp/control …


Detailed course schedule

A detailed schedule of the course can be found here; topics are just indicative while days and teachers are correct up to some last minute change (they will be notified to you by email).

Note: Lecture timetable interpretation
* On Tuesday, in V.S8-A, starts at 08:15, ends at 10:15
* On Friday, in V.S8-A, starts at 10:15, ends at 13:15
Date Day Time Room Teacher Topic
07/03/2017 Tuesday 08:15 - 10:15 V.S8-A Matteo Matteucci Course Introduction, Robotics and Cognitive Robotics
10/03/2017 Friday 10:15 - 13:15 -- -- -- No Lecture --
14/03/2017 Tuesday 08:15 - 10:15 -- -- -- No Lecture --
17/03/2017 Friday 10:15 - 13:15 V.S8-A Matteo Matteucci Cognitive architectures: Deliberative vs Reactive
21/03/2017 Tuesday 08:15 - 10:15 -- -- -- No Lecture --
24/03/2017 Friday 10:15 - 13:15 -- -- -- No Lecture --
28/03/2017 Tuesday 08:15 - 10:15 V.S8-A Matteo Matteucci Deliberative Models: Planning Introduction
31/03/2017 Friday 10:15 - 13:15 V.S8-A Matteo Matteucci Deliberative Models: Planning with GPS and Prodigy
04/04/2017 Tuesday 08:15 - 10:15 V.S8-A Matteo Matteucci Deliberative Models: Planning Examples
07/04/2017 Friday 10:15 - 13:15 V.S8-A Matteo Matteucci Deliberative Models: PDDL with Examples
11/04/2017 Tuesday 08:15 - 10:15 V.S8-A Matteo Matteucci Reactive Models: Behavior Based Robotics
14/04/2017 Friday 10:15 - 13:15 -- -- -- No Lecture --
18/04/2017 Tuesday 08:15 - 10:15 -- -- -- No Lecture --
21/04/2017 Friday 10:15 - 13:15 V.S8-A Matteo Matteucci Reactive Models: Subsumption Architecture
25/04/2017 Tuesday 08:15 - 10:15 -- -- -- No Lecture --
28/04/2017 Friday 10:15 - 13:15 -- -- -- No Lecture (suspension) --
04/05/2017 Thursday 15:00 - 18:00 V.08 Roberto Basili Natural Language Processing
05/05/2017 Friday 09:30 - 12:30 V.08 Roberto Basili Natural Language Processing
05/05/2017 Friday 13:30 - 15:30 V.08 Roberto Basili Natural Language Processing
09/05/2017 Tuesday 08:15 - 10:15 V.S8-A Andrea Bonarini Non verbal human-robot interaction
12/05/2017 Friday 10:15 - 13:15 V.S8-A Andrea Bonarini Non verbal human-robot interaction
16/05/2017 Tuesday 08:15 - 10:15 V.S8-A Andrea Bonarini Non verbal human-robot interaction
19/05/2017 Friday 10:15 - 13:15 V.S8-A Matteo Matteucci Neural Models
23/05/2017 Tuesday 08:15 - 10:15 V.S8-A Matteo Matteucci Neural Models
26/05/2017 Friday 10:15 - 13:15 V.S8-A Andrea Bonarini Non verbal human-robot interaction
30/05/2017 Tuesday 08:15 - 10:15 V.S8-A Matteo Matteucci Neural Models
02/06/2017 Friday 10:15 - 13:15 -- -- -- No Lecture --
06/06/2017 Tuesday 08:15 - 10:15 V.S8-A Marco Ciccone (Deep) Learning Approaches
09/06/2017 Friday 10:15 - 13:15 V.S8-A Marco Ciccone (Deep) Learning Approaches
13/06/2017 Tuesday 08:15 - 10:15 V.S8-A Marco Ciccone (Deep) Learning Approaches
16/06/2017 Friday 10:15 - 13:15 V.S8-A Marco Ciccone (Deep) Learning Approaches
20/06/2017 Tuesday 08:15 - 10:15 -- -- -- No Lecture --
23/06/2017 Friday 10:15 - 13:15 V.S8-A Matteo Matteucci Student presentation: Marta Pagani
28/07/2017 Friday 14:30 - 17:30 V07 Matteo Matteucci Students presentation: Florin Varga, Elcin Kulatu
14/09/2017 Thursday 09:30 - 17:30 V.S8-B Matteo Matteucci Students presentation: Emanuele Dalla Longa, Davide Urzino, Roza Shafiei, Federico Milani, Ashok Kumar Yarramneni

Course Evaluation

The course grading is split in a standard written exam (70% of the grade) and a practical activity (30% of the grading):

  • Written examination covering the whole program up to 25/32
  • Small practical project or seminar on a course topic graded up to 7/32
  • Final score will be the sum of the two grades up to 32/32

Possible course projects and seminar activities will be presented later during the semester.

Teaching Material

The course material comprises slides from the teachers and scientific literature, both provided in the following.

Teacher Slides

In the following you can find the lecture slides used by the teacher and the teaching assistants during classes.

Here the lectures about classical cognitive architectures, i.e., deliberative and reactive approaches:

The following are the slides on Neural Networks and Deep Learning:

The following are the slides on Natural Language Processing for Human Robot Interaction:

The following are the slides on Non Verbal Human Robot Interaction:

Students Slides

In the following you can find the slides presented to the class by students as part of their evaluation.

Books and Papers

For some of the following paper I provide the link to the journal website. For the most of them you can access the PDF if you are connected to the polimi network or using the polimi proxy.

  • Simon Russell, Peter Norvig. "Artificial Intelligence: A Modern Approach". Chapter 11: Planning, pages 375-416.Pearson, 2010. [1]
  • Valentino Braitenberg. "Vehicles: Experiments in synthetic psychology". Cambridge, MA: MIT Press, 1984.
  • Rodney A. Brooks. "Elephants don't play chess", Robotics and Autonomous Systems, Volume 6, Issues 1–2, June 1990, Pages 3-15. [2]


Exam Samples and Results

The following are few past exams, do not make any assumption on the topics you should prepare and about the level of details of the questions from these texts, they are not a statistically significan sample from the possible exams texts: