Introduction to Cognitive Science - Syllabus
Embark on a profound academic exploration as you delve into the Introduction to Cognitive Science course () within the distinguished Tribhuvan university's CSIT department. Aligned with the 2065 Syllabus, this course (CSC-255) seamlessly merges theoretical frameworks with practical sessions, ensuring a comprehensive understanding of the subject. Rigorous assessment based on a 60+20+20 marks system, coupled with a challenging passing threshold of , propels students to strive for excellence, fostering a deeper grasp of the course content.
This 3 credit-hour journey unfolds as a holistic learning experience, bridging theory and application. Beyond theoretical comprehension, students actively engage in practical sessions, acquiring valuable skills for real-world scenarios. Immerse yourself in this well-structured course, where each element, from the course description to interactive sessions, is meticulously crafted to shape a well-rounded and insightful academic experience.
- The student will gain an introductory understanding of what it means to say that intelligence is computational
- The student will:
- Acquire a good understanding of what an algorithm is and learn how to implement algorithms in the programming language LISP
- Develop an introductory understanding of formal models for computation, the limits of computation, the Chomsky hierarchy, and the Turing-Church hypothesis
- The student will study some of the modern attempts to demonstrate a computational model for intelligence through an introduction to the discipline of artificial intelligence, including introductions to knowledge representation, search, and artificial neural networks.
- Finally, the student will explore some of the positions taken in the ongoing discussion of this issue. In Philosophy and Linguistics, we will begin with Descartes, and look (and discuss) Turing, Gelernter, Newell and Simon, Penrose, Searle, and others, finishing with a partial response to Descartes given to us by Chomsky and others.
Units
Cognitive Science and other Science, Descartes, Marr, Algorithms and Computation, Turing’s response to Descartes, Application related system in the Cognitive Science.
Brief Introduction to Artificial Intelligence
History and background of Artificial Intelligence, Knowledge representation, Human information processing and problem solving, Search, Expert system, Introduction of Neural Networks.
Computation
Introduction, Basic Model for Computation, The Turing Machine, Computational and Language: the Chomsky hierarchy, The Physical Symbols Systems Hypothesis, Illustration of practical examples.
Approaches
The connectionist approach, Different models and tool: Gelernter, Penrose, Pinker, Searle; Response to Descartes: Natural Language Processing, Parameters in the Natural Language Processing.