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Fundamentals of Our Thinking 2

Data

Official data in SubjectManager for the following academic year: 2024-2025

Course director

Number of hours/semester

lectures: 12 hours

practices: 0 hours

seminars: 0 hours

total of: 12 hours

Subject data

  • Code of subject: OXFGD2-z-T
  • 1 kredit
  • Dentistry
  • Optional modul
  • spring
Prerequisites:

-

Course headcount limitations

min. 5 – max. 15

Available as Campus course for . Campus-karok: BTK GYTK TTK

Topic

The course aims to introduce students to the fundamental principles and complexities of human thought. Using a holistic approach, the course will explore the related problems of how correct inference and cognition are possible, applying the tools and results of philosophy, mathematics and neuroscience. Human thinking is based on similarity, analogy, which is the basis of the concepts of differential diagnosis and differential therapy in the field of medicine. In both clinical practice and research, the correct inference and the correct interpretation of data are very important in order to make possible what is perhaps the ultimate goal of science, successful prediction.

In the second semester, we will compare artificial and biological networks and their associated learning processes. We will examine the mind-brain problem, how the brain as a biological object and thinking can be related. We will briefly address the basic cognitive abilities that underlie the processes of thinking and cognition, and the adaptive and learning abilities of biological systems. At the end of the semester, we will briefly discuss the relationship between non-scientific thinking and the arts.

Lectures

  • 4. Similarities and differences between biological and artificial networks. - Péczely László Zoltán
  • 3. Adaptation: regulation and learning. - Péczely László Zoltán
  • 2. Hierarchically nested systems. - Péczely László Zoltán
  • 1. Brain-mind problem. - Péczely László Zoltán
  • 5. Cognitive functions: perception, attention, decision-making, strategy, memory, thinking, - Péczely László Zoltán
  • 6. Learning in biological systems I. - Péczely László Zoltán
  • 7. Learning in biological systems II. - Péczely László Zoltán
  • 8. Biological constraints on neural network models of cognitive function. - Péczely László Zoltán
  • 9. Algorithms, randomness and prediction. - Péczely László Zoltán
  • 10. Prediction and the brain. - Péczely László Zoltán
  • 11. Is only scientific thinking possible? Thinking as poetry. - Péczely László Zoltán
  • 12. Thinking and art. - Péczely László Zoltán

Practices

Seminars

Reading material

Obligatory literature

Literature developed by the Department

lecture slides

Notes

Recommended literature

Peter Norvig, Stuart J. Russell: Artificial Intelligence: A Modern Approach

Conditions for acceptance of the semester

Writing an essay by the end of the semester.

Mid-term exams

Peter Norvig, Stuart J. Russell: Artificial Intelligence: A Modern Approach

Making up for missed classes

not necessary

Exam topics/questions

Are the same as lecture topics.

Examiners

Instructor / tutor of practices and seminars

Rólunk