Cognitive Science & Artificial Intelligence (CS390L)

Course Information

Title: Cognitive Science and Artificial Intelligence
Institution: Metropolitan State University of Denver
Course ID: CS 390L [54899]
Semester: Fall 2017
Meetings: Mondays & Wednesdays 2:00PM - 3:50PM
Location: AES 285
Hours: Credit Hours: 4
Contact Hours: 60
Additional Student Work Hours:
    120 hours minimum outside of class
Prerequisites: CS 2050 and MTH 3170, each with a grade of "C" or better. (CS 3210 is strongly recommended.)
Moodle Site:
Instructor: Dr. Jody Paul (schedule & office hours)
E-mail: jody @ computer . org
Office: AES 200X   (303-615-0978)
Campus Mail: Campus Box 38
Students are required to attend all sessions during the first week of class. (See: University policy on Class Attendance)

Catalog Text

This course provides an overview of the interdisciplinary field of cognitive science -- the study of mind and its functions -- with emphasis on the areas of the field involving artificial intelligence.

This course builds on students' computer science backgrounds to understand the integration of component disciplines that comprise cognitive science, notably: artificial intelligence, linguistics, psychology, philosophy, neuroscience, and anthropology. Emphases are given to artificial intelligence and to the use of human behavioral artifacts to reveal underlying aspects of cognition.

Behavioral Learning Objectives:

  • Describe the purview of cognitive science
  • Identify the key constituent disciplines of cognitive science
  • Interpret alternative models of cognition
  • Illustrate applications of cognitive science principles
  • Formulate hypotheses regarding models of cognition
  • Propose computational experiments to test cognition hypotheses
  • Compare artificial intelligence approaches to cognitive modeling
  • Assess ethical issues concerning cognitive science and artificial intelligence



Cover of Mind Mind: Introduction to Cognitive Science, Second Edition
by Paul Thagard (2005) ISBN: 026270109X,
Cover of book by Lieber Can Animals and Machines Be Persons?: A Dialogue
by Justin Leiber (1985) ISBN: 0872200027,
Cover of Predictably Irrational Predictably Irrational, Revised and Expanded Edition: The Hidden Forces That Shape Our Decisions
by Dan Ariely (2010) ISBN: 0061353248,
Cover of Inevitable Illusions Inevitable Illusions: How Mistakes of Reason Rule Our Minds
by Massimo Piattelli-Palmarini (1996) ISBN: 047115962X
Cover of Programming Clojure Third Edition OR Cover of Programming Clojure Programming Clojure (either Third Edition or Second Edition)

The newer Third Edition is preferred. Although it won't be officially released until October, a beta version is now available. Because it is in ebook form only, the earlier Second Edition is also acceptable for this semester, with the caveat that it is not as up-to-date.

Programming Clojure, Third Edition
by Alex Miller, Stuart Halloway, and Aaron Bedra (2017) ISBN-10: 1680502468,

Programming Clojure, Second Edition
by Stuart Halloway and Aaron Bedra (2012) ISBN-10: 1934356867,


Cover of Dynamic Memory Revisited

Dynamic Memory Revisited
by Roger C. Schank (1999) ISBN: 0521633982,
OPTIONAL — Model theory of memory and learning

Cover of Companion to Cognitive Science A Companion to Cognitive Science
edited by William Bechtel & George Graham (1999) ISBN: 0631218513,
OPTIONAL — Extensive collection; broad coverage
Cover of Bermúdez book

Cognitive Science: An Introduction to the Science of the Mind, Second Edition
by José Luis Bermúdez (2014) ISBN: 1107653355,
OPTIONAL — Comprehensive overview of Cognitive Science; textbook-style

Cover of Friedenberg book

Cognitive Science: An Introduction to the Study of Mind, Third Edition
by Jay Friedenberg & Gordon Silverman (2015) ISBN: 1483347419,
OPTIONAL — Comprehensive overview of Cognitive Science; textbook-style

Cover of Gilovich book

How We Know What Isn't So: The Fallibility of Human Reason in Everyday Life
by Thomas Gilovich (1993) ISBN: 0029117062,
OPTIONAL — Additional examples of human reasoning

Class Policies

Class Sessions & Websites

You are expected to prepare in advance for class sessions (reading, exercises, etc.), to participate in class discussions and activities, and to make in-class presentations. Participation in class discussions and activities is mandatory and constitutes part of the overall grade for the course.

A substantial amount of information is disseminated during class sessions or via the course website. You are responsible for knowing this information whether or not you attended the sessions or accessed the website. Note in particular that the textbooks and references provide some but not all of the information necessary to successfully complete the course.

In addition to important course and domain information, the course support website also provides the vehicle for managing assignments and assessment.

Successful software engineering is rarely a solitary endeavor. Collaboration and teamwork are the norms. Individual performance may be recognized, but the entire project team is judged by the team’s collective performance. Acquisition of team-oriented skills and practices is integral to this course and comprises part of the assessment.

Scoring & Grading

There are scored and un-scored activities in the course. Students are expected to attempt all activities. Not submitting a scored activity earns a score of zero for that activity. Activities have different maximum point values indicating the relative weight of each. The total course score is the sum of points of all scored activities divided by sum of their maximum point values. The final course grade is determined by associating letter grades with total course score as shown.

            A : 90% ≤ score
            B : 80% ≤ score < 90%
            C : 70% ≤ score < 80%
            D : 60% ≤ score < 70%
            F : score < 60%

Assignments & Projects

Assignments and projects represent your opportunity to practice applying the concepts, thereby enhancing your understanding, and to demonstrate your knowledge of the concepts and their application. Details regarding assignments and projects will be provided in class or on the course support website.


Every assignment and project turned in must include a section (maximum 150 words) labeled “Reflection” in which you are expected to reflect on the experience of working on the assignment or project and describe your personal insights and observations associated with the experience. This reflection is required whether or not the assignment specification mentions it explicitly. Reflections comprise a portion of the score of every assignment and project.

Online Submission

Assignments must be turned in using the course Moodle website unless explicitly specified otherwise. In particular, e-mail and hard-copy will not be accepted in lieu of online submission.

The Moodle “assignment” activity allows the use of working-drafts, but such drafts are not automatically submitted. Assignment attempts in DRAFT status will result in no earned score for the assignment. You must explicitly submit an assignment before the deadline for it to be considered for scoring and credit.

To submit an assignment entry for scoring:

  1. You must click the Submit button for that assignment. Use of the Submit button indicates that the assignment is intended to be scored.
  2. You must verify and accept any subsequent attestation that states that the work is entirely your own unless (a) included works of others are explicitly cited and (b) other contributors are explicitly referenced.
Deliverable Formats

When available, the Online text field of a Moodle assignment should be used for text-based responses and for reflections. File attachments to Online text are generally not acceptable.

Formats of files turned in for assignments must not depend on specific operating system or commercial software.

  • Examples of generally acceptable formats: ASCII or UNICODE UTF-8 text, HTML, PDF, GIF, JPEG, PNG.
  • Examples of specifically unacceptable formats: Microsoft Word, Apple Pages, Microsoft PowerPoint, Apple Keynote, Microsoft Excel, Apple Numbers.
  • Acceptable formats for archives include only tar and zip.

If a specific archive or file format is required it will be explicitly specified.

A deliverable submitted in an unacceptable format is equivalent to no submission at all. If unsure about the acceptability of afile format, please check with the instructor prior to submission and well before the deadline.

Deadlines (Due Dates/Times)

Deliverables associated with assignments may be submitted for scoring at any time prior to the published deadline.

No assignment deliverables will be accepted after the published deadline.

Because there are so many risks to completion and submission, you are strongly encouraged to target completion and submission of assignments no less than 24 hours prior to the published deadline. Computer systems and networks often experience "down times" and are likely to be strained during the 24-hour period immediately preceding a published deadline; thus, you should not depend on such systems, including the course support servers, to be consistently available during that period. Further, the instructor may not be available to address questions directly referencing that specific assignment in the last 24 hours.

Illness, crises, and emergency situations will be dealt with on a case-by-case basis in accordance with University, College, and Departmental policies.

Collaboration & Citation of Sources

Collaboration is encouraged and regarded as an essential aspect of learning computer science. Collaboration and discussion with fellow students and instructors concerning course information, materials, assignments, projects, proofreading, concept exploration and studying for exams is strongly encouraged. You are not expected to learn the course content or work on assignments and projects in complete isolation.

That said, in order to provide fair assessment for grading, the work you turn in must reflect your own efforts. You must write up your own submissions, reflecting your individual effort, for every assignment you turn in to be assessed, even if the solution results from collaborative effort. In your submission, you must credit the people with whom you worked or consulted.

If you consult any sources, your submission must explicitly reference those sources and indicate where and how they apply.

Remember that you must write and turn in a personal reflection for every collaborative effort, as well as every individual effort.

Collaboration during exams is never acceptable.

Academic Dishonesty

Turning in work that includes quotations without corresponding citations, does not properly cite references, or does not credit collaborators, will be treated as an act of academic dishonesty. Failing to abide by examination policies will be treated as an act of academic dishonesty. All incidents of suspected dishonesty will be reported to the Chair of the department and the Dean of the college. Consequences may include a score of 0 on the assignment, a grade of "F" for the course, academic probation, or dismissal from the institution. This is a very serious matter and should not be taken lightly. If you have any uncertainty or concerns, please discuss them with your instructor or your advisor.

Official Information

Withdrawal dates and procedures
• 100% refund: Sun. August 27
• 50% refund: Wed., September 6
• Last Day for W: Wed. November 8
Holiday information: Labor Day: September 4 (Campus Closed) Fall Break: Nov 20-26 (No classes, Campus Open except for Thanksgiving Day – Nov. 23 )

A copy of the official syllabus for the course which includes the Learning Objectives for the course is provided at

Students are responsible for full knowledge of the provisions and regulations pertaining to all aspects of their attendance at MSU Denver, and should familiarize themselves with the following policies:

   Students should be aware that any kind of withdrawal can have a negative impact on some types of financial aid, including scholarships.

For a complete description of these policies go to: