Logic of Computation and Information
A.Y. 2021/2022
Learning objectives
By locating computational and information systems in their conceptual and technical evolution, students will gain working knowledge of the underlying logics and will understand how they are used for many applications in other sciences. The course includes activities for understanding different formal models of computation and for the representation of information transmission, both single and multi-agent. Such notions and methods will be valuable in any activity requiring advanced reasoning and problem-solving abilities in the computational domain.
Expected learning outcomes
Knowledge acquisition and understanding:
The course provides knowledge of formal methods and logics in the area of computing and information essential for the analysis and understanding of new software and data-intensive science methodologies. The course provides basic knowledge and technical skills in the following topics:
- Logic and computability
- Turing Computability
- Logics of Program Correctness
- Process Algebra
- Temporal Logics
- Logics of Information
- Multi-Agent Systems
Skills acquisition and ability to apply knowledge:
At the end of the course, students are expected to be able to:
- formally identify classes of computable functions and problems;
- formally define properties of computational processes;
- formally express reasoning about computational processes;
- formally describe informational structures and reasoning on them.
The course provides knowledge of formal methods and logics in the area of computing and information essential for the analysis and understanding of new software and data-intensive science methodologies. The course provides basic knowledge and technical skills in the following topics:
- Logic and computability
- Turing Computability
- Logics of Program Correctness
- Process Algebra
- Temporal Logics
- Logics of Information
- Multi-Agent Systems
Skills acquisition and ability to apply knowledge:
At the end of the course, students are expected to be able to:
- formally identify classes of computable functions and problems;
- formally define properties of computational processes;
- formally express reasoning about computational processes;
- formally describe informational structures and reasoning on them.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
During the ongoing covid emergency, the course syllabus will be maintained with the following changes made to enhance the effectiveness of the online version of the course, which was originally designed for face-to-face teaching.
The lessons will be held in dual mode. The face-to-face lessons will allow the participation of students connected with MSTeams as well as students in the classroom. The recordings of the lessons will remain available for the entire semester.
Online environments used:
Moodle: https://labonline.ctu.unimi.it/course/view.php?id=391
Teams: keycode in Moodle
Students wishing to participate in face-to-face lessons must refer to the following University provisions:
https://www.unimi.it/en/study/bachelor-and-master-study/following-your-programme-study/teaching-activities-campus
Students wishing to participate in MSTeams lessons must refer to the following technical guides:
https://www.unimi.it/en/study/student-services/technology-and-online-services/microsoft-office-365-education
To participate in the exam sessions, students must refer to the following provisions:
https://www.unimi.it/en/study/bachelor-and-master-study/following-your-programme-study/sitting-exams
The lessons will be held in dual mode. The face-to-face lessons will allow the participation of students connected with MSTeams as well as students in the classroom. The recordings of the lessons will remain available for the entire semester.
Online environments used:
Moodle: https://labonline.ctu.unimi.it/course/view.php?id=391
Teams: keycode in Moodle
Students wishing to participate in face-to-face lessons must refer to the following University provisions:
https://www.unimi.it/en/study/bachelor-and-master-study/following-your-programme-study/teaching-activities-campus
Students wishing to participate in MSTeams lessons must refer to the following technical guides:
https://www.unimi.it/en/study/student-services/technology-and-online-services/microsoft-office-365-education
To participate in the exam sessions, students must refer to the following provisions:
https://www.unimi.it/en/study/bachelor-and-master-study/following-your-programme-study/sitting-exams
Course syllabus
MODULE A
1. Computing and Decidability
2. Mechanical Computation
3. Logics of Program Correctness
MODULE B
4. Basics of Process Algebra
5. Temporal Logics
MODULE C
6. Logics of Information
7. Multi-Agent Systems
8. Logics of Communication
1. Computing and Decidability
2. Mechanical Computation
3. Logics of Program Correctness
MODULE B
4. Basics of Process Algebra
5. Temporal Logics
MODULE C
6. Logics of Information
7. Multi-Agent Systems
8. Logics of Communication
Prerequisites for admission
Successful completion of the course Logical Methods.
Teaching methods
Frontal lectures and tests.
Link Moodle: https://labonline.ctu.unimi.it/course/view.php?id=391
Link Moodle: https://labonline.ctu.unimi.it/course/view.php?id=391
Teaching Resources
G.Primiero. On the Foundations of Computing. OUP, 2019. [selected chapters]
M.Huth, M.Ryan, Logic in Computer Science, CUP 2004. [selected chapters]
C. Bayer, J.P. Katoen, Principles of Model-Checking, MIT Press, 2008. [selected chapters]
L. Floridi, The Logic of Being Informed, Logique Et Analyse, vol 196, pp. 433-460 (2006)
P. Allo, The Logic of Being Informed Revisited and Revised, Philosophical Studies, 153(53), pp.417-434 (2011)
G.Primiero, An Epistemic Logic for Becoming Informed, Synthese, 167:2, pp.363-389, 2009.
M. D'Agostino, An informational view of Classical Logic, Theoretical Computer Science, vol. 606, pp. 79-97, 2015.
G. Primiero, A logic of negative trust, Journal of Applied Non-Classical Logic, 2020 https://doi.org/10.1080/11663081.2020.1789404.
M.Huth, M.Ryan, Logic in Computer Science, CUP 2004. [selected chapters]
C. Bayer, J.P. Katoen, Principles of Model-Checking, MIT Press, 2008. [selected chapters]
L. Floridi, The Logic of Being Informed, Logique Et Analyse, vol 196, pp. 433-460 (2006)
P. Allo, The Logic of Being Informed Revisited and Revised, Philosophical Studies, 153(53), pp.417-434 (2011)
G.Primiero, An Epistemic Logic for Becoming Informed, Synthese, 167:2, pp.363-389, 2009.
M. D'Agostino, An informational view of Classical Logic, Theoretical Computer Science, vol. 606, pp. 79-97, 2015.
G. Primiero, A logic of negative trust, Journal of Applied Non-Classical Logic, 2020 https://doi.org/10.1080/11663081.2020.1789404.
Assessment methods and Criteria
For attending and non-attending students: Learning assessment will be through a written exam at the end of the course. Multiple choice tests and open questions are aimed to broadly verify the understanding of concepts and definitions taught during the course whereas exercises are designed to evaluate problem solving skills. Optional in addition to the test and only for attending students: a written paper on a subject and with characteristics agreed with the teacher.
Unita' didattica A
M-FIL/02 - LOGIC AND PHILOSOPHY OF SCIENCE - University credits: 3
Lessons: 20 hours
Unita' didattica B
M-FIL/02 - LOGIC AND PHILOSOPHY OF SCIENCE - University credits: 3
Lessons: 20 hours
Unita' didattica C
M-FIL/02 - LOGIC AND PHILOSOPHY OF SCIENCE - University credits: 3
Lessons: 20 hours
Professor(s)
Reception:
Tuesdays, 14:00-17:00. Students are kindly asked to get in touch by email to confirm date and hour.
Teams/Slack