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Design and Evaluation of Artificial Cognitive Systems
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Design and Evaluation of Artificial Cognitive Systems
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Academic year 2022/2023
- Course ID
- INF02
- Teacher
- Antonio Lieto (Titolare del corso)
- Degree course
- PhD in Computer Science
- Teaching period
- Da definire
- Type
- A scelta dello studente
- Credits/Recognition
- 6
- Course disciplinary sector (SSD)
- INF/01 - informatics
- Delivery
- Tradizionale
- Language
- Inglese
- Attendance
- Facoltativa
- Type of examination
- Relazione finale
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Sommario del corso
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Course objectives
Students will learn how computational models of cognition can be used to help us in understanding human intelligence and in making progress towards more advanced AI systems.
Content:
1. Introduction to cognitive artificial systems
2. Design Paradigms in Cognitive Systems: from the Cybernetics to the origins of Artificial Intelligence
3. Modelling Paradigms: Cognitivism and computationalism, connectionism, dynamical systems and enactivism
4. Unified theories of cognition: Cognitive Architectures
5. Role of a cognitive architecture in AI and Cognitive Modelling
6. Design characteristics of cognitivist and emergent architectures
8. Example cognitive architectures (e.g. SOAR, ACT-R, LIDA, CLARION, and others)
9. Towards a Standard/Common Model of the Mind
10. Differences between Cognitive Systems and the so-called “Cognitive Computing” Systems
11. Open problems in AI and Cognitive Systems communities
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Program
This course will introduce the main modelling methods, paradigms and technologies involved in the design of cognitive artificial systems. Students will understand the theoretical and technical challenges involved in modelling and building systems that can reason, solve problems, acquire and use knowledge and make decisions in real-life environments. A particular emphasis will dedicated to the Cognitive Architectures: software adopted in a variety of fields (ranging from robotics to video games) explicitly implementing human-like heuristics and decision procedures coming from the experimental results of the cognitive science.
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Course delivery
Frontal lessons (with slides) with associated seminars. During the course there will be bi-weekly collective readings and exercises.
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Learning assessment methods
Students should present a theoretical or computational project using one of the cognitive architectures that will be presented during the course.
Suggested readings and bibliography
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Antonio Lieto, (2021) Cognitive Design for Artificial Minds, Routledge Taylor & Francis.
Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017) Building machines that learn and think like people Behavioral and Brain Sciences, 40, (PDF)
David Vernon, (2014) Artificial Cognitive Systems: A Primer, MIT Press.Allen Newell (1990), Unified Theories of Cognition, Harvard University Press.
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Notes
For more information please contact Antonio Lieto at "lieto At di Dot unito Dot it"
- Enroll
- Closed
- Enrollment opening date
- 01/03/2020 at 00:00
- Enrollment closing date
- 31/12/2022 at 23:55
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