Introduction to cognitive science 1000-2M11WK
The course is aimed at introducing students to issues of symbolic mental representations in cognitive science. The cognitive science paradigm will be discussed , taking into account how human behavior is explained in terms of information processing. Particular mental representations will be discussed from the perspective of the major debates about the nature of mind, the explanation of the behavior and ways of modeling the action of mind.
On mind, machines, algorithms and thinking. What does cognitive science owe to ancient Greeks?
What is this thing called Cognitive Science? The Computational - Representational Understanding of Mind (CRUM).
Mental representations (cognitive representations)
Propositions - cognitive representations based on logic
Rules as cognitive representations
Concepts as cognitive representations
Analogies as cognitive representations
Perception: mental images as cognitive representations
Wason’s Selection Task - an example of a debate on the explanation of empirical results using various types of mental representations
Connectionism – subsymbolic (network based) representations as cognitive representations
Summary - review and evaluation of the six approaches to the issue of mental representations
Challenges facing cognitive science
Evolutionary - computational theory of mind and the future of cognitive science
Type of course
Learning outcomes
Knowledge:
1. understands well the role and meaning of the computer metaphor both as an empirical hypothesis in cognitive science and analogy in the preparation of artificial intelligence programs.
2. has a basic knowledge of the main types of mental representations and mental procedures postulated in cognitive science.
3. knows the basics of the empirical methodology of cognitive science.
4. knows the assumptions and goals of modeling cognitive behavior of people using the methods of artificial intelligence.
5. knows the psychological roots of tools and concepts used in artificial intelligence and in the representation of knowledge.
6. knows the cognitive roots of the human-computer interaction field.
Skills:
1. can explain selected human behaviors in terms of information processing (K_U11).
2. analyzes individual methods of artificial intelligence due to its suitability for modeling particular cognitive behaviors of a human being (K_U12).
3. has in-depth communication skills with experts in the fields of cognitive science, cognitive psychology and cognitive neuroscience who do not have IT knowledge (K_U11).
4. can describe the tools of artificial intelligence and computational models of human behavior (K_U12).
Competence:
1. has elementary preparation for cooperation in teams conducting cognitive research (K_K02).
2. knows the limits of his/her own knowledge and understands the need for further education, including the acquisition of knowledge from outside the field of computer science (K_K01).
3. is able to precisely formulate questions that serve to deepen one's understanding of a given topic, in particular when dealing with experts in cognitive science, cognitive psychology and cognitive neuroscience (K_K02).
4. can present IT issues related to cognitive science (K_K06).
Assessment criteria
- class attendance (at seminars)
- elaboration of selected articles, preparation of its presentations and giving talks in the seminar
- written exam on the knowledge of the issues presented during lectures
Bibliography
Paul Thagard (2005) "Mind. Introduction to Cognitive Science", 2nd Edition, MIT Press.
Additionally:
Steven Pinker (2009) "How the Mind Works", W.W. Norton & Company, Inc.
Edward Nęcka, Jarosław Orzechowski, Błażej Szymura (2013) "Cognitive Psychology" (in Polish), PWN.
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
- Bachelor's degree, first cycle programme, Computer Science
- Master's degree, second cycle programme, Computer Science
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: