COGS 201 / 3.0

Cognition and Computation

Winter Term - 2017

Prerequisites:   COGS 100/3.0 or PSYC 100 or PSYC 221; CISC 121 or CISC 124 or CISC 102 or some software programming experience can be helpful

 

Instructor:

Farhana H. Zulkernine, PhD, PEng

Assistant Professor

Coordinator, Cognitive Science Program
756 Goodwin Hall, School of Computing, Queen's University
Kingston, Ontario, Canada K7L 2N8

E-mail: Farhana at cs dot queensu dot ca (farhana@cs.queensu.ca)

Website: http://research.cs.queensu.ca/home/farhana/
Tel: 1 (613) 533-6426


 

This course is an introduction to the computational aspects of the mind. Can thought be understood in terms of computation? How do we process logic in planning and problem solving? The theory of cognition compares representation and metal processes with data structures and computation. This course explores that theory by taking the students through an exciting journey of very simple programming to understand the human thought process. The latter part of the course explores other computational and theoretical aspects of cognition such as information theory and behaviourism, cognitive architectures and computational modeling of cognition, perception and memory processes.

The students should leave with a good understanding of computational aspects of human cognition acquired through some hands-on fun programming exercises which requires no previous programming experience. They would also learn the importance of computational modeling and simulations, and get a brief overview of the major cognitive models and architectures.

 

Learning Outcomes

Course Learning Outcomes: http://www.cs.queensu.ca/students/undergraduate/CLO.php#COGS201

Syllabus

COGS 201 W/3.0: Cognition and Computation

Unit 1: Computation depicted as the core essence of Cognitive Science as thoughts are merely the products of mental processes as they are applied to perceived information in the mind.  This is illustrated through simple logic programs that simulate human thoughts in problem solving, planning, decision making and language.
Unit 2: Introduction to information theory, cognitive modeling techniques Physical Symbol System and Artificial Neural Network models with example models from the literature.
Unit 3: Overview of Cognitive Architectures. Includes student group presentation of the different architectures.

 

 

Class time and location
Days & Times Room Dates
Mon 1:30pm -2:30pm DUNNING RM10 Jan 09 - Apr 07
Wed 12:30pm -1:30pm DUNNING RM10 Jan 09 - Apr 07
Fri  11:30am -12:30pm DUNNING RM10 Jan 09 - Apr 07

 

Office Hour

Wednesday 1:30pm - 2:30pm. Otherwise contact the TA to setup meeting times.

 

Marking

Assignments            20%

Online Quizzes       20%

Group Project         10%

Midterm                  20%

Final exam              30%

 

Course Details

Details about the course content can be found at the OnQ website.

 

Textbooks

 

Supplementary Book