CSC 480 – Artificial Intelligence
Instructor: Adam Hartley
Email: hartlead@mountunion.edu
Office: KHIC 041
Office Hours: 2:00-3:00 MWF; 12:30-1:30 TR; by appointment; or whenever my door is open!
Textbooks:
Course Objectives:
\(M\epsilon\tau\alpha\beta\acute{\alpha}\lambda\lambda o \nu \ \grave{\alpha}\nu\alpha\pi\alpha\acute{\upsilon}\epsilon\tau\alpha\iota\)
(Even as it changes, it stands still.) — Heraclitus
My aim is to show that the heavenly machine is not a kind of divine, live being, but a kind of clockwork (and he who believes that a clock has a soul attributes the maker’s glory to the work), insofar as nearly all the manifold motions are caused by a most simple and material force, just as all motions of the clock are caused by a single weight. —Johannes Kepler (letter to Herwart von Honenburg, 1605)
After the completion of this course, the student should be able to:
Identify and discuss the major areas of study within artificial intelligence
Explain in detail several approaches currently used when creating intelligent agents
Distinguish between informed search and uninformed search
Distinguish between breadth-first search and depth-first search
Explain how resolution is used to resolve a propositional logical argument with multiple variables.
Be able to implement simple intelligent agents in a general purpose programming language
Develop a robust understanding of ethical questions and topics current in the industry
Course Outline
A rough outline of the pace of the course and topics covered is below. Each activity is due by the start of class one week after it is introduced.
| Week # | Topic |
|---|---|
| 1 | Chapter 1 |
| 2 | Chapter 27 |
| 3 | Chapter 2 |
| 4 | Chapter 3 |
| 5 | Chapter 3 / 4 |
| 6 | Chapter 4 |
| 7 | Chapter 5 |
| 8 | Chapter 5 / 6 |
| 9 | Chapter 6 |
| 10 | Chapter 7 |
| 11 | TBD |
| 12 | TBD |
| 13 | TBD |
| 14 | Presentations |
| 15 | Presentations |
Grading
| Grade Range | Letter Grade |
|---|---|
| 100%-94% | A |
| 93.9%-90% | A- |
| 89.9%-87% | B+ |
| 86.9%-84% | B |
| 83.9%-80% | B- |
| 79.9%-77% | C+ |
| 76.9%-74% | C |
| 73.9%-70% | C- |
| 69.9%-67% | D+ |
| 66.9%-64% | D |
| 63.9%-60% | D- |
| <60% | F |
The assignments for the course are divided into a few categories:
Quizzes 20%:
- Paper quizzes designed to test qualitative knowledge of course materials will be given frequently.
Final Project: 30%.
The capstone assignment for the class is a presentation detailing a personal exploration of a subtopic in artificial intelligence. This can either be a topic that was covered in class, pursued in more depth, or another topic outside the scope of the class. These topics could include (but are not limited to):
Generative AI
Classical AI
Historical AI
AI programming languages / Systems
Confluence of AI with other fields
The findings will be presented to the class at the end of the semester and should include a demonstration and code that implements the method or program explored.
More information about the final project will be provided as we get underway.
Homework / Labs 20%:
- There will be frequent lab work during the class. Sometimes it will be necessary to complete parts of the assignment outside of class.
Ethics / News Presentation 20%:
On Fridays, there will be time for discussions on recent and current events and trends involving AI. Each student will find two topics (industry or mainstream news, or similar) regarding artificial intelligence that have ethical implications for us and our industry. Students will reserve time on a Friday in advance to present the topic to the class and lead the subsequent discussion. These presentations should contain the equivalent of 5-10 slides of information regarding the topic, including the context of the topic and answering the following questions:
To what extent has AI been used?
How was AI intended to be used?
What were the alternatives if AI was not used?
How was the use of AI perceived by the public/industry peers?
What is the ethical aspect of the topic?
Assignments may occasionally include optional extensions that will be graded for extra credit. These will generally require additional discussion with the instructor. Come to office hours or schedule an individual time!
In general, no other extra credit work will be assigned.
Collaboration Policy
The field of science is almost entirely collaborative. If students wish to collaborate on solving exercises or activities outside of class, this is allowed and encouraged under the condition that you explicitly note with whom you collaborated. Each student must turn in their own copy of the work, each copy listing the collaborators. Please limit group work to two or three students. Each student is individually responsible for the course information. Collaboration is not allowed during exams.
Late Policy
Each 24 hours, an assignment is past due, it is worth 10% fewer points. After 72 hours, the assignment is worth zero points. Extra credit work, if applicable, isn’t accepted past-due. The exams and final project will generally not be accepted late. In the case of an emergency or extended complications that would prevent exam attendance or inability to participate in the class, contact the instructor as early as possible so that other arrangements may be made.
Communication Policy
I will strive to be available and accessible to every student in each of my classes. To facilitate better understanding of when and how I will be available, I will lay out a few expectations. In general, I will not check or respond to emails before 8:00 A.M. or after 5:00 P.M. on weekdays. Otherwise, I will try to reply to any emails or Teams messages within 24 hours. Please don’t hesitate to send a follow-up message if I haven’t responded to you during this window; there’s always a chance your email was missed, however unlikely. In general, there will be no message regarding the class that is so important that it can’t wait until the morning. We’ll work it out.
Technology Requirements
College coursework requires students to be responsible with reading and assignments, checking email and D2L frequently, and staying in regular communication with instructors. Technology access will be important for success. To participate in learning activities and complete assignments, you will need:
Access to a working computer that has a current operating system with updates installed
Reliable Internet access and a Mount Union email account
A current Internet browser that is compatible with D2L
Please contact the IT Help Desk at 330.829.8726 or helpdesk@mountunion.edu if you need assistance with obtaining or using a device, any necessary software, or internet access at any time during this semester.
Please bring your laptop to class, we will make extensive use of in-class time for lab work.
Artificial Intelligence Policy
Artificial intelligence is a rapidly evolving field, and there are now multiple programs (e.g., ChatGPT and Bard) that can interact with users via “natural” conversations and rapidly generate output, including art, essays, and computer code. Programs such as these will continue to evolve and be utilized in professional settings, and you can and should become familiar with them in the course of your undergraduate studies. At the same time, in-demand employees are those who have skills (to not use an AI when doing so would expose proprietary information to the creator of the AI, to debug AI-generated code when it doesn’t get it quite right, to modify output from AI for subtly different use cases, to perform tasks independent of AI when appropriate…) and the clarity of thought and ability to communicate effectively and effortlessly. Your college education is a time to develop these abilities and using AI as a crutch can hinder that process.
That said, usage of AI tools is explicitly allowed in this course. However, usage of AI tools, for purposes of assisting research, generative text, writing code, etc. MUST be accompanied by an experience report, which is an explanation of the following things:
What tool did you use?
For what portions of your assignment did you use the tool?
What was your experience using the tool? Was it easy or hard to get the results you desired?
How useful did you find the tool?
Did the AI tool help you understand the material or present it in a way that you found more useful?
Do you think using the AI tool enhanced or inhibited your learning process?
The experience report is required even if you do not use any output from the AI tool. Using AI tools without reporting their use in the form of an experience report is considered a breach of academic honesty.
The experience reports (in whole or in part) may be discussed in class, but the professor will anonymize and summarize them beforehand.
Please note that neither reporting the use of AI nor the exact answers to the questions of the experience report (as long as they’re truthful) will adversely affect your grade in any way. Neither the use of AI tools nor their abstinence will put you at a technical advantage or disadvantage regarding how assignments are graded. However, you are still responsible for the information presented in this class, and there will be some points (like in-class quizzes and discussions) where AI tools will not be readily available. Furthermore, if you submit work with AI assistance that happens to be incorrect, it will be graded as-is and marked accordingly.
Please remember that this policy does not necessarily reflect the policies and outlook of other Mount Union professors and is currently only applicable to CSC 480. Please continue to respect differing AI policies at this university.
Accessibility
The University of Mount Union values disability as an important aspect of diversity and is committed to providing equitable access to learning opportunities for all students. Student Accessibility Services (SAS) is the campus office that collaborates with students who have disabilities to provide and/or arrange reasonable accommodations based upon appropriate documentation, nature of the request, and feasibility. If you have, or think you have, a temporary or permanent disability and/or medical diagnosis in any area such as, physical or mental health, attention, learning, chronic health, or sensory, please contact SAS. The SAS office will confidentially discuss your needs, review your documentation, and determine your eligibility for reasonable accommodations. Accommodations are not retroactive, and the instructor is under no obligation to provide accommodations if a student does not request accommodation or provide documentation. Students should contact SAS to request accommodations and should discuss their accommodations with their instructor as early as possible in the semester. You may contact the SAS office by phone at (330) 823-7372; or via e-mail at studentaccessibility@mountunion.edu.
Additional University Policies
See https://www.mountunion.edu/syllabus for policies and information that are universally applicable to all courses at the University of Mount Union.