Cognitive Science Study Guide: Understanding the Mind and the Machine

Cognitive Science focuses on understanding the human mind and its relation to artificial systems.
The primary inquiry explores the mechanics of how the brain performs complex tasks such as thought, memory storage, and imagination.
A foundational experiment involves thinking of a favorite ice cream without speaking, raising questions about where that image is stored and why humans can imagine a specific item (like a chocolate ice cream scoop) even if they have never seen that exact instance before.
A central goal is to determine if a computer can replicate these biological cognitive processes.

Scrambled Text Recognition: Humans possess the ability to read sentences where letters are scrambled, such as "I cna raed tihs snetecne wtih no pobelrm."
- This occurs because the brain does not consciously read every letter.
- The brain functions as a predictive engine, anticipating words based on context and existing knowledge.
Visual Perception: When presented with an image, different people may see different things despite their eyes sending the exact same visual information to the brain.
- This phenomenon demonstrates that the difference in perception lies within the brain's processing, not the sensory input itself.

The brain is more than a biological organ; it performs extraordinary tasks including:
- Seeing and hearing.
- Remembering and predicting.
- Imagining and learning.
- Solving problems.
- Creating language.
- Understanding emotions.
Most of these processes occur without conscious notice. The greatest mystery in science is not what the brain does, but exactly how it does it.
Machine Intelligence vs. Human Thinking: There is a distinction between a machine calculating or searching (like Google) and a machine actually thinking.
- Key questions for Artificial Intelligence (AI) include whether a robot can recognize a face, learn language, pay attention, understand sarcasm, forget memories, or imagine the future.
- This overlap of inquiry is where AI meets Cognitive Science.

Course Objectives:
- To study the basic concepts and approaches within the field of cognitive science.
- To apply models of planning, reasoning, and learning in cognitive applications.
- To analyze language and semantic models of cognitive processes.
Course Outcomes:
- Demonstrating qualitative and quantitative skills and critical thinking by applying methodologies to real-world cognitive applications.
- Acquiring knowledge in language processing and understanding.
- Learning the cognitive processes of humans, robots, and other intelligent systems.

Module 1: Introduction to Cognitive Science:
- Fundamental concepts and the role of computers in the field.
- Applied cognitive science and its interdisciplinary nature.
- Structure and constituents of the brain and a brief history of neuroscience.
- Mathematical models, analysis of brain signals, and processing of sensory information.
Module 2: Memory:
- Types of memory and memory models.
- Visual imagery and problem-solving techniques.
- Overall evaluation of the cognitive approach.
Module 3: Network Approach:
- Principles and characteristics of Artificial Neural Networks (ANN).
- Conceptions of neural networks, including ANN typologies.
- Backpropagation and convergent dynamics.
- Evaluating the connectionist approach.
- Semantic networks: characteristics and evaluation.
Module 4: Cognitive Science in Linguistics:
- Importance and nature of language.
- Language use in primates, language acquisition, and deprivation.
- The role of grammar in cognition and linguistics.
- Intersection of neuroscience, AI, and linguistics.
- Speech recognition and evaluation of Natural Language Processing (NLP).
Module 5: Cognitive Science in Robotics:
- Affordances, direct perception, and Ecological Psychology.
- Affordance learning in robotics.
- Child development versus robotic development.
- Attention concepts: human visual attention and computational models of attention.
- Applications of computational models of attention.

Bermúdez, José Luis: Cognitive Science: An Introduction to the Science of the Mind, Cambridge University Press, 2014.
Stillings, Neil; Weisler, Steven E.; Chase, Christopher H.; Feinstein, Mark H.: Cognitive Science: An Introduction, Second Edition, MIT Press, 1995.
Mallick, Pradeep Kumar; Borah, Samarjeet: Emerging Trends and Applications in Cognitive Computing, IGI Publishers, 2019.
Fromkin, Rodman, and Hyams: An Introduction to Language, Boston, MA: Thomson Wadsworth, 9th edition, 2011.
Stuart J. Russell, Peter Norvig: Artificial Intelligence - A Modern Approach, Third Edition, Pearson Publishers, 2015.

Evaluation Parameters:
- Mid Exam I: $25\%$ weightage.
- Quizzes (Minimum 2): $20\%$ weightage.
- Assignment(s) (Minimum 2): $10\%$ weightage.
- End Semester Exam: $45\%$ weightage.
- Total Marks: $100\%$ .
Weekly Timetable Highlights:
- ISC213/ISC213 (T) Lectures: Wednesday, Thursday, and Friday sessions.
- Instructors listed in the timetable include: Dr. Riyasudheen T K (RTK), Dr. Jisha Mariyam John (JMM), Dr. Krishnendhu S.P (KSP), Dr. Syamala S (SLS), Dr. P. Victer Paul (VP), Dr. Dhakshayani J (DKJ), Dr. Gayathri Varma (GTV), and Ms. Priyamol (PT).

Modern AI, including tools like ChatGPT, still struggles with several key human attributes:
- Emotions and sarcasm.
- Common sense and reasoning.
- Hallucinations (generating false information).
Humans continue to outperform AI in many cognitive tasks, which the course aims to explore.

Cognitive Science is ultimately the human brain attempting to understand itself through the study of memory, language, attention, learning, and intelligence.