Cognitive processes modelling I

The course introduces students to the main approaches to the cognitive systems modeling, provides a broad overview of the modeling methods and their applications, with a focus on dynamical systems perspective. We also explore the need and possibilities of their integration for modeling complex cognitive phenomena.

Cognitive systems are characterized by their ability to functionally adapt to their environments, which in turn allows them to react to the changes in their surroundings or initiate actions of their own. Mechanisms of functional adaptation of this kind are found in a wide variety of phenomena spanning multiple scales: biological systems (single cells, cell colonies, organized tissues, systems such as immune system etc.), whole organisms, higher animals and humans with their mental processes, social groups exhibiting cultural adaptation, and populations exhibiting macro-dynamics. Modeling such phenomena requires an interdisciplinary approach in which different fields of study stimulate each other: psychological and biological discoveries inspire the development of new mathematical models and computational methods, which often find applications outside of the original domain. Developed models help to formulate hypotheses, plan further experiments, verify theories, and augment the overall understanding of cognitive processes. Last but not least, models of the cognitive processes are often inspirations for developing artificial cognitive systems, such as autonomous robots or software agents, which extend human agency in the world.

The aim of this course is to give an overview of the main paradigms, approaches and methods used to model processes of such systemic adaptation. We show how different methods relate to each other and how they can be applied to uncover different aspects of the studied phenomena. We focus on methodological issues and illustrate them with examples of concrete models and concrete research from multiple domains such as motor development, decision making, language acquisition, social coordination, cultural evolution etc.

Upon successful completion of the course you will:

be able to describe the theory and philosophy behind the main paradigms in cognitive modeling, their origins and assumptions (K_W01, K_W02, K_W08)

know multiple methods used to model cognitive systems, and understand their strengths and weaknesses (K_U01)

know which experimental paradigms in cognitive science can be a source of data for which types of cognitive modeling (K_W07)

know the cognitive scientific terminology pertaining to modeling and be able to assess the use of cognitive models in a scientific project and/or paper (K_W08, K_U01)

be able to communicate concepts related to cognitive modeling within an interdisciplinary team (K_W08, K_U07)

be able to find information pertinent to main models in cognitive science, understand the fast pace of changes in the field (K_U08, K_K01)

be sensitive to the use of artificial systems and their relation to human agency within relevant ecosystems (K_K02, K_K07)

80% Written exam covering the lectures and selected literature

20% Quizzes & Homeworks

Additionally, students can improve their grade by actively participating in class discussions during lectures.

Attendance to the lecture is obligatory, 2 unexcused absences are allowed.

Basics of cognitive psychology and basic understanding of statistics. Course indicated for 3-5th year students.

Students must respect the principles of academic integrity. Cheating and plagiarism (including copying work from other students, internet or other sources) are serious violations that are punishable and instructors are required to report all cases to the administration.