COSC 4368 --- Fundamentals of Artificial Intelligence Spring 2024 ( Dr. Eick )

last updated: April 30, 2024

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Basic Course Information

2024 COSC 4368 Syllabus
class meets: MO/WE 2:30-4p
class room: SEC 103
Instructor: Dr. Christoph F. Eick
office hours (online using 4368 MS Team and F2F): MO 4-5p WE 9-10a
office: 573 PGH
TA: Md. Mahin
TA office hour: MO&WE 12:30-1:30p
TA office: online
TA Email:
TA: Raunak Sarbajna
TA office hour: TU&TH 9-10a
TA office: online
TA Email: rsarbajn@CougarNet.UH.EDU
cancelled classes: none at the moment
makeup classes: none at the moment
lectures (and laps) taught by others: March 18: Raunak, March 25: Mahin, April 8: Raunak and April 22: Mahin.

Topics Covered in COSC 4368

The course will give an introduction to AI and it will cover Problem Solving (covering chapter 3, 4 in part, 5, and 6 in part, centering on uninformed and informed search, adversarial search and games, A*, alpha-beta search, and constraint satisfaction problems), Learning (covering learning from examples (chapter 18 in part), deep learning (extra material) and a lot reinforcement learning (chapter 21, chapter17 in part;)), Reasoning and Learning in Uncertain Environments (covers chapters 13, 14, 15 in part, and 20 in part, centering on basics in probabilistic reasoning, naive Bayesian approaches, belief networks and maybe Hidden Markov Models (HMM)). Moreover, the course will cover Evolutionary Computing, Game Theory, Ethics for AI, Deep Learning centering on autoencoders, diffusion models and U-Net relying on other teaching material.

Course Materials

Recommended Text:
S. Russell and P. Norvig, Artificial Intelligence, A Modern Approach, Fourth Edition,
Prentice Hall/Allyn&Bacon, December 2020,
Link to Textbook Homepage.

Course Elements

There will be a midterm and a final exam in Spring 2024. This semester we will have 3 problem sets which contain tasks which require programming, and tasks which use AI tools, and an essay writing task. There will be six tasks in the three problem sets! There will be a 7-week group project which will start approx. February 20, 2024. Finally, each student will be involved in a single group homework credit (GHC) task (which are also group tasks), whose solution needs to be presented during the COSC 4368 lecture. Each group will solve a different "kind of homework" problem!

News COSC 4368 Spring 2024

Important 2024 Dates for COSC 4368

We., January 17, 2:30p: First Course Lecture
We., March 6, 2:30p: Midterm Exam (2024 Review List; March 4, 2024 Review, Solution Sketches MT2024)
March 11+13: Spring Break: no lecture
Mo., March 18: Lecture and Task3 Lab, centering on Neural Networks, taught by Raunak.
We., March 27: Lecture on Autoencoder and Task4 Lab taught by Md. Mahin.
Sa., April 6, 11:59p: Deadline Task4
Su., April 14, 11:59p: Deadline Group Project
Mo., April 15: Lecture and Task5 Lab, centering on Diffusion Models, taught by Raunak.
Mo., April 22, 11:59p: Deadline Task6
Su., April 28, 11:59p: Deadline Task5
Mo., April 29, 2:30p: Last lecture
We., May 1, 11:59p: Deadline Task 7
Mo., May 6,2-4p: Final Exam in F (Fleming) 160 (Final 2024 Review List (updated on May 1), April 29 Review for Final Exam)

Tentative Course Organization

1. Introduction to AI
2. Search
3. Evolutionary Computing
4. Game Theory (very short)
5. Reinforcement Learning
6. Supervised Learning, centering on Basics and Neural Networks
7. Deep Learning (will cover autoencoders, diffusion models, and briefly U-Net, and language models)
8. AI Politics and Societal/Ethical Aspects of AI
9. Reasoning in Uncertain Environments
10. Planning (only if enough time; not covered in 2023 and 2024)

2024 Problem Sets and Group Project

Problem Set1 (two individual tasks centering on search)

Problem Set2 (individual tasks centering on neural networks and deep learning)

Group Project: Reinforcement Learning in a 3-Agent Transportation World (2024 PD-World, 2024 Groups, February 26-April 12, 2024)

Problem Set3: Ethics and Societal Aspects of AI and Belief Networks (Task 6 Grading Rubric; Task 7: take a look at Khadija's How to create and use BBNs in Netica video))

2024 Policies Concerning Late Submissions

Submissions up to 24 hours late receive a 8% penalty; submissions 24 hours and 1 minute to 48 hours late receive a 20% penalty, and submissions received more than 48 hours late will not be graded.

2024 Group Homework Credit Tasks

2024 Groups

Tasks (will be posted at least 5 days before the presentation date):
Group A will present on We., Feb. 7 (task can be found as a slide in search1.pptx)
Groups B and C Tasks (both groups will present on Mo., Feb. 12)
Group D Task (will present on We., Feb. 14)
Group E Task and Group F Task (both groups will present on Feb. 28)
Group G Task (will present on March 4)
Group H will make a presentation and lead an in-class discussion centering on "Using ChatGPT in COSC Courses" and Group I Task (both groups will present on March 20)
Group J "ImageFX: Demo & Brief Look under its Hood" and Group K Task) will present on April 3
Group M will give a presentation and lead a discussion about AI Arms Races on April 24!
Groups L, O, and N Task (group L will present of April 17, and groups O will present on April 24, Group N will give a presentation on April 29)

2024 COSC 4368 Polls

January 24 Poll Results

Undergraduate Research in Dr. Eick's Research Group

2024 UH-DAIS Research Overview
Some Summer 2024 Undergraduate Research Topics (only Topic1 is still available)

COSC 4368 Lecture Transparencies

2024 Lecture Attendance

Attendance counts 3% towards your overall course grade for the Spring 2024 teaching of the course. F2F Attendance will be taken Jan. 29-April 29, 2024; that is twice in January, 8 times in February, 5 times in March, and 9 times in April for a total of 24; number of lectures you attended will be converted as follows into a number grade:
23-24:94, 22:93, 21:92, 20:89, 19:86, 18:83, 17:80, 16:77, 15:74, 14:71, 13:68, 12:65, 11:62, 10:59, 9:56, 8:53, 7:50, 6:47, 0-5:44.

Old 2024 News Items

Reinforcement Learning Videos

Please view the following 3 videos:
  • Siraj Raval: How to use Q Learning in Video Games Easily (7 minutes, will show the first 3:30 on February 20, 2019)
  • Richard Sutton: Deconstructing Reinforcement Learning (about 50 minutes)
  • Eric Guimarães:Demo Q-Learning in a GridWorld(2 minutes)
  • 2019 4368 Review Solution Sketches

    Solution Sketches April 8, 2019 Review for Midterm2 Exam


    COSC 2320 or COSC 2430.

    Other Matial Related to COSC 4368

    Some Summaries of the COSC 4368 Questionnaire Responses from January 23, 2019

    2002 Exam Solution Sketches

    March 9, 2022 Midterm Exam A Solution Sketches
    March 9, 2022 Midterm Exam B Solution Sketches


    Translation number to letter grades:
    A:100-92 A-:92-88 B+:88-84 B:84-80 B-:80-76 C+:76-71
    C: 71-66 C-:66-62 D+:62-58 D:58-54 D-:54-50 F: 50-0

    Only machine written solutions to homeworks and project reports are accepted. Be aware of the fact that our only source of information is what you have turned in. If we are not capable to understand your approach or solution, you will receive a low score. Moreover, students should not throw away returned assignments or tests.

    Students may discuss course material and homeworks, but must take special care to discern the difference between collaborating in order to increase understanding of course materials and collaborating on the homework / course project itself. We encourage students to help each other understand course material to clarify the meaning of homework problems or to discuss problem-solving strategies, but it is not permissible for one student to help or be helped by another student in working through homework problems and in the course project. If, in discussing course materials and problems, students believe that their like-mindedness from such discussions could be construed as collaboration on their assignments, students must cite each other, briefly explaining the extent of their collaboration. Any assistance that is not given proper citation may be considered a violation of the Honor Code, and might result in grade reduction, obtaining a grade of F in the course, and in further prosecution.

    2020 Reviews and Exams

    Midterm1 Exam (Mo., March 2, 2020 Review List, February 26, 2020 Review for Midterm1 Exam)

    Midterm2 Exam (Mo., April 13, 2020 Review List, April 8, 2020 Review for Midterm2 Exam (only 40% of the review questions will be discussed on April 8!)).

    Final Exam (Mo., May 4, 2p, Review List 2020 Final Exam, April 27, 2020 Review for Final Exam, Solution Sketches May 6, 2019 Final Exam)

    2021 Final Exam and Review for it

    Final Exam (We. May 12, 2022 2p, First Draft of Review List 2021 Final Exam (will be finalized by May 6 the latest, May 3 2021 Review for Final Exam, Solution Sketches May 6, 2019 Final Exam)

    2023 Problem Sets and Group Project

    Problem Set1 (two individual tasks centering on search; updated on Feb. 2)

    Problem Set2 (two individual tasks centering on supervised learning and generators/autoencoders; Steve's 2023 Task3 Lecture, Task3 Jupyter Notebook, Task4 Jupyter Notebook; you find the March 22 Autoencoder lecture in the deep learning slides below)

    Problem Set3 (Task5 Grading Rubric; Task6: take a look at Khadija's How to create and use BBNs in Netica video))

    2023 Group Project (February 24-April 23, 2023): Learning Paths in a 2-Agent 3D Transportation World using Reinforcement Learning (2023 PD World, 2023 Teams)

    Tentative Weights in 2023 (subject to change): Problem Set Tasks: 30%, Group Project:17%, Midterm Exam: 21%, Final Exam: 26%, GHC: 3%, Attendance: 3%.

    2023 Group Homework Credit Tasks

    2023 Groups

    Group A and Group B Tasks (both groups will present on We., Feb. 8; Group B will present a revision of their solution on We., Feb. 15)
    Group C Task (will present on Mo., Feb. 13)
    Group D Task (will present on We., Feb. 22)
    Group E Task (will present on We., March 1)
    Group F Task (will present on Mo., March 6 (and maybe March 20))
    Group G and H Task (will present on Mo., March 27)
    Group I Task (will present on Mo., April 3)
    Group J will make a 10-13 minute presentation "Will China be the Number 1 in AI", followed by a discussion, on We., April 12!
    Group N will discuss ChatGPT Mo., April 17
    Group K will give a presentation on Robot Soccer on Mo., April 24
    Group O will give a presentation on 'AI and Fake News' on We., April 26
    Group L Task (will present on Mo., May 1)
    Group M will give a presentation about the European AI Ethics Guidelines on May 1


    Finally, Congratulations go to all 4368 students who graduated in Spring 2020 semester!!! This slide is part of the "must see" Spring 2020 NSM Graduation Celebration video.