IS 698 - Special Topics in Information Systems: Artificial Intelligence (Spring 2024)

Information Systems Department
University of Maryland Baltimore County
Baltimore, Maryland 21250
Departmental Office: Room ITE 404, ph. 410-455-3206

Course Description

In this course, students will learn the fundamentals of artificial intelligence (AI), including search, constraint satisfaction, and reinforcement learning. The course will also cover reasoning and decision-making via propositional logic, probability, and Bayesian networks. To connect AI to its broader context, students will learn about the history of AI, ethical and safety concerns, and the benefits and risks of AI technologies.

Student learning outcomes: By the end of this course, you will be able to:

The learned skills of formalizing real-world problems quantitatively, solving them via AI algorithms, and writing code to implement the proposed solutions, are vital across the computing, information, and engineering sectors.

Course Delivery: Online, asynchronous, weekly modules will be delivered via Blackboard. Each module will include assigned readings, a video lecture, multichoice questions, and online discussions.

Instructor: Dr. James Foulds
Instructor email: jfoulds [at] umbc [dot] edu
Instructor office hours: Thursdays 3:00 - 4:00 pm ET, online (Blackboard Collaborate) (other times by appointment)


Required Textbook

Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (4th Edition), Pearson, ISBN-13: 978-0134610993, ISBN-10: 0134610997. is the course textbook. The textbook is made available to you for the course via Blackboard.

Reading assignments will be given for each module, which are very important for your learning, and for making the best use of our limited time. These weekly readings are therefore required.

Course Requirements and Grading

Homeworks and Individual Projects

The homework assignments will consist primarily of written problems and calculations. The two individual projects will involve java programming to solve AI problems. The individual projects will be graded based on the correctness of the solution for new test cases.

Final Exam

The exam will be administered as a Blackboard assignment, released on Monday 5/13/2024 and will be due on Sunday 5/19/2024, 11:59 pm. It will assess the learning goals that are stated in each module throughout the course. Anything that is in the readings but not in lesson slides will not be assessed in the exam.

Multichoice Questions on Blackboard

Each weekly module will include multichoice questions that assess understanding of the reading and the lesson material in the lecture video / slides. Although they will be graded for accuracy, unlimited attempts are allowed before the weekly deadline (Sunday, 11:59 pm).


In this course, participation means more than just showing up. It also refers to contributing to everyone's learning, through active engagement in discussions, which will be associated with each module. You are required to post in the discussion by Friday (11:59 pm ET), and post a reply that responds to another post by Sunday (11:59 pm ET). To obtain full credit, posts and replies must (1) be at least two paragraphs long, (2) demonstrate understanding of the material, (3) display critical thinking, (4) provide justification supporting all claims, and (5) include citations to the academic literature or other reputable sources. They will be graded based on these criteria (equal weight for each).


With respect to final letter grades, UMBC's Catalog states that an A indicates "superior" achievement; B, "good" performance; C, "not satisfactory"; D, "unacceptable"; F, "failure." There is specifically no mention of any numerical scores associated with these letter grades. Below is how grades may be assigned based on your final points, accumulated over the semester. Grades will be assigned using a plus/minus system. It is university policy that A+, D+, and D- are not assigned. I do not grade on a curve, so that everyone in the class has the opportunity to succeed.

Final Grade Letter Grade Points when calculating GPA
91 - 100 A 4.0
89 - 90.99 A- 3.7
87 - 88.99 B+ 3.3
81 – 86.99 B 3.0
79 - 80.99 B- 2.7
77 – 78.99 C+ 2.3
71 – 76.99 C 2.0
69 - 70.99 C- 1.7
60 – 68.99 D 1.0
0 – 59.99 F 0.0

Homework and Exam Policies


Chapter numbers in the readings refer to the Russell and Norvig textbook unless otherwise specified.
Date (Monday) Summary Details Assessment Required reading
1/29/2024Week 1Course Introduction Course overview, overview of AI, history of AI Ch 1 "Introduction." You can skip over Ch 1.2 "The Foundations of Artificial Intelligence"
2/5/2024Week 2 Uninformed Search Intelligent agents, search, depth-first and breadth-first search Ch 3, up to and including Ch 3.4 "Uninformed Search Strategies"
2/12/2024Week 3 Heuristic Search and Adversarial Search Backtracking DFS, uniform cost search, greedy search, A*, minimax searchHW1 due Ch 3.5 "Informed (Heuristic) Search Strategies," up to and including Ch 3.5.3 "Search Contours." Ch 5, "Adversarial Search and Games," up to and including Ch 5.2.2 "Optimal Decisions in Multiplayer Games"
2/19/2024Week 4 Alpha-Beta Pruning, Constraint Satisfaction 1 Alpha-beta search, constraint satisfaction problem (CSP) formulation From Ch 5.2.3 "Alpha–Beta Pruning," up to and including Chapter 5.2.4 "Move Ordering." Ch 6, "Constraint Satisfaction Problems," up to the end of Chapter 6.1 "Defining Constraint Satisfaction Problems"
2/26/2024Week 5 Constraint Satisfaction 2 Backtracking search for CSPs, constraint propagation, interleaving search and inference Individual project 1 due From Ch 6.2 "Constraint Propagation: Inference in CSPs," up to and including Chapter 6.3 "Backtracking Search for CSPs"
3/4/2024Week 6 Propositional Logic knowledge-based agents, logical inference, entailment, resolution Ch 7 "Logical Agents," up to the end of Ch 7.5.2 "Proof by Resolution"
3/11/2024Week 7 AI and Society AI ethics principles, lethal autonomous weapons, self-driving cars, privacy, AI fairness and bias HW2 due Ch 27.3 "The Ethics of AI," up to and including Ch 27.3.3, "Fairness and Bias"
3/18/2024Week 8 Spring Break (no module)
3/25/2024Week 9 Probability Random variables, conditional and joint probabilities, independence, Bayes rule Ch 12 "Quantifying Uncertainty"
4/1/2024Week 10 Reinforcement Learning Model-based vs. model-free reinforcement learning, passive vs. active RL, temporal difference learning, exploration vs. exploitation, Q-learningIndividual project 2 due Ch 22 "Reinforcement Learning, up to and including Ch 22.3 "Active Reinforcement Learning"
4/8/2024Week 11 Bayesian networks Bayesian networks, d-separation, Markov blankets Ch 13 "Probabilistic Reasoning," up to and including Ch 13.2.1 Conditional Independence Relations in Bayesian Networks
4/15/2024Week 12 Modeling with Bayesian networks MPE, MAP, modeling examples HW3 due Ch 13.2.3 Bayesian Nets with Continuous variables and Ch 13.2.4 "Case study: Car insurance"
4/22/2024Week 13 Inference in Bayesian networks Variable elimination, bucket elimination Ch 13.3 "Exact Inference in Bayesian Networks," up to and including "Ch 13.3.2 "The Variable Elimination Algorithm"
4/29/2024Week 14 Bayesian inference for machine learning Frequentist vs Bayesian inference, MAP vs. MLE, full posterior vs. point estimates, posterior predictive HW4 due Cowles, K. et al. (2019). What is Bayesian Analysis? Published at , and Bishop, C. M. (2013). Model-based machine learning. Phil. Trans. R. Soc. A, 371(1984).
5/6/2024Week 15 Topic models and mixed membership models LSA/PLSA, Genetic admixtures, LDA, collapsed Gibbs sampler Blei, David M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77-84
5/13/2024 Exam week Final Exam Final exam held on Blackboard, due Sunday 5/19/2024.

The schedule may be subject to change. The summary and details columns are only a guideline of the content likely to be covered, and the dates on which material is covered may shift.

COVID-19 Policies

Please see this Google doc for UMBC Policies and Resources during COVID-19.

Academic Integrity

UMBC's policies on academic integrity will be strictly enforced (see the University System of Maryland's policy document, UMBC's academic integrity overview page, and the UMBC catalog). In particular, all of your work must be your own. Acknowledge and cite source material in your papers or assignments. While you may verbally discuss assignments with your peers, you may not copy or look at anyone else's written assignment work or code, or share your own solutions. Any exceptions will result in a zero on the assessment in question, and may lead to further disciplinary action. Some relevant excerpts from UMBC's policies, as linked to above, are:

The use of software tools to obfuscate your work in order to hide plagiarism is wrong, and is strictly prohibited.

Policy on ChatGPT and other Large Language Models (LLMs)

The use of language models such as ChatGPT for assignments will be strictly regulated. Your work must be your own. While language models can be lightly used as a writing aid, their use must be limited to a small part of any solution and they must not contribute to the substance of your answer. Any use of these tools as a writing aid must be declared in your submission, with an explanation of why the work is your own and why the use does not constitute plagiarism. You must also submit a log of all queries used in your submission. If you have any questions, please check with us.

Diversity Statement on Respect

Students in this class are encouraged to speak up and participate during our meetings. Because the class will represent a diversity of individual beliefs, backgrounds, and experiences, every member of this class must show respect for every other member of this class. (Statement from California State University, Chico’s Office of Diversity and Inclusion).

Accessibility and Disability Accommodations, Guidance and Resources

Accommodations for students with disabilities are provided for all students with a qualified disability under the Americans with Disabilities Act (ADA & ADAAA) and Section 504 of the Rehabilitation Act who request and are eligible for accommodations. The Office of Student Disability Services (SDS) is the UMBC department designated to coordinate accommodations that would create equal access for students when barriers to participation exist in University courses, programs, or activities.

If you have a documented disability and need to request academic accommodations in your courses, please refer to the SDS website at for registration information and office procedures.

SDS email:
SDS phone: (410) 455-2459

If you will be using SDS approved accommodations in this class, please contact me (instructor) to discuss implementation of the accommodations. During remote instruction requirements due to COVID, communication and flexibility will be essential for success.

Counseling Center

Diminished mental health can interfere with optimal academic performance. The source of symptoms might be related to your course work; if so, please speak with me. However, problems with other parts of your life can also contribute to decreased academic performance. UMBC provides cost-free and confidential mental health services through the Counseling Center to help you manage personal challenges that threaten your personal or academic well-being.

Remember, getting help is a smart and courageous thing to do -- for yourself and for those who care about you. For more resources get the Just in Case mental health resources Mobile and Web App. This app can be accessed by clicking:

The UMBC Counseling Center is in the Student Development & Success Center (between Chesapeake and Susquehanna Halls). Phone: 410-455-2472. Hours: Monday-Friday 8:30am-5:00pm.

Family Educational Rights and Privacy Act (FERPA) Notice

Please note that as per federal law we are unable to discuss grades over email. If you wish to discuss grades, please come to office hours.

Sexual Assault, Sexual Harassment, and Gender Based Violence and Discrimination

UMBC Policy in addition to federal and state law (to include Title IX) prohibits discrimination and harassment on the basis of sex, sexual orientation, and gender identity in University programs and activities. Any student who is impacted by sexual harassment, sexual assault, domestic violence, dating violence, stalking, sexual exploitation, gender discrimination, pregnancy discrimination, gender-based harassment, or related retaliation should contact the University’s Title IX Coordinator to make a report and/or access support and resources. The Title IX Coordinator can be reached at or 410-455-1717.

You can access support and resources even if you do not want to take any further action. You will not be forced to file a formal complaint or police report. Please be aware that the University may take action on its own if essential to protect the safety of the community. If you are interested in making a report, please use the Online Reporting/Referral Form. Please note that, if you report anonymously, the University’s ability to respond will be limited.

Notice that Faculty are Responsible Employees with Mandatory Reporting Obligations:

All faculty members are considered Responsible Employees, per UMBC’s Policy on Sexual Misconduct, Sexual Harassment, and Gender Discrimination. Faculty and teaching assistants therefore required to report all known information regarding alleged conduct that may be a violation of the Policy to the Title IX Coordinator, even if a student discloses an experience that occurred before attending UMBC and/or an incident that only involves people not affiliated with UMBC. Reports are required regardless of the amount of detail provided and even in instances where support has already been offered or received.

While faculty members want to encourage you to share information related to your life experiences through discussion and written work, students should understand that faculty are required to report past and present sexual harassment, sexual assault, domestic and dating violence, stalking, and gender discrimination that is shared with them to the Title IX Coordinator so that the University can inform students of their rights, resources, and support. While you are encouraged to do so, you are not obligated to respond to outreach conducted as a result of a report to the Title IX Coordinator.

If you need to speak with someone in confidence, who does not have an obligation to report to the Title IX Coordinator, UMBC has a number of Confidential Resources available to support you:

Other Resources:

Child Abuse and Neglect:

Please note that Maryland law and UMBC policy require that faculty report all disclosures or suspicions of child abuse or neglect to the Department of Social Services and/or the police even if the person who experienced the abuse or neglect is now over 18.

Pregnant and Parenting Students

UMBC’s Policy on Sexual Misconduct, Sexual Harassment and Gender Discrimination expressly prohibits all forms of discrimination and harassment on the basis of sex, including pregnancy. Resources for pregnant, parenting and breastfeeding students are available through the University’s Office of Equity and Civil Rights. Pregnant and parenting students are encouraged to contact the Title IX Coordinator to discuss plans and ensure ongoing access to their academic program with respect to a leave of absence – returning following leave, or any other accommodation that may be needed related to pregnancy, childbirth, adoption, breastfeeding, and/or the early months of parenting.

In addition, students who are pregnant and have an impairment related to their pregnancy that qualifies as disability under the ADA may be entitled to accommodations through the Office of Student Disability Services.

Religious Observances & Accommodations

UMBC Policy provides that students should not be penalized because of observances of their religious beliefs, and that students shall be given an opportunity, whenever feasible, to make up within a reasonable time any academic assignment that is missed due to individual participation in religious observances. It is the responsibility of the student to inform the instructor of any intended absences or requested modifications for religious observances in advance, and as early as possible. For questions or guidance regarding religious observances and accommodations, please contact the Office of Equity and Civil Rights at

Hate, Bias, Discrimination and Harassment

UMBC values safety, cultural and ethnic diversity, social responsibility, lifelong learning, equity, and civic engagement.

Consistent with these principles, UMBC Policy prohibits discrimination and harassment in its educational programs and activities or with respect to employment terms and conditions based on race, creed, color, religion, sex, gender, pregnancy, ancestry, age, gender identity or expression, national origin, veterans status, marital status, sexual orientation, physical or mental disability, or genetic information.

Students (and faculty and staff) who experience discrimination, harassment, hate, or bias based upon a protected status or who have such matters reported to them should use the online reporting/referral form to report discrimination, hate, or bias incidents. You may report incidents that happen to you anonymously. Please note that, if you report anonymously, the University’s ability to respond may be limited.

Campus Resources