Syllabus: CAP 5605 Artificial Intelligence Spring 2025
Overview:
This class aims to introduce the essential concepts of artificial intelligence and the design of intelligent agents. It provides an in-depth exploration of fundamental problem-solving techniques and knowledge representation frameworks within the field of AI. Students will become familiar with the AI programming language LISP, as well as techniques like state-space analysis, problem reduction, heuristic and brute-force search methods, planning strategies, two-player game theory, and recent advancements in game AI. In the realm of knowledge representation and reasoning, the course focuses both propositional and first-order logic, along with their respective inference algorithms. Lastly, students will be exposed to probabilistic approaches in AI, including Bayesian Networks, Causal Inference, and Machine Learning algorithms.
Prerequisites:
This course requires knowledge of basic computer science, math, algorithms and complexity, and programming principles.
Optional Textbook:
Artificial Intelligence: A Modern Approach, Author: Stuart Russell, Peter Norvig, Publisher: Pearson, Edition: 4th, Year Published: 2021, Copyright Year: 2021.
Programming Language:
LISP
Logistics:
Time: Monday and Wednesday 1:20PM - 2:35PM
Location: HCB 0103
Instructor: Ang Li (Email: angli at cs dot fsu dot edu)
The instructor’s office hour is Wednesday 3:00PM-4:00PM at 166 Love Building.
Teaching Assistant: TBD
Course Website: https://www.causalds.org/teaching/cap-5605
Grading Policy:
Grades will be computed based on the following factors:
Homework 24% (30% for CAP 4601)
Challenge Homework Questions 6% (Extra credits for CAP 4601)
Midterm 30%
Final 40%
Letter Grades: The letter grades will be assigned according to the following criteria, and if necessary, the grades will be curved upwards.
Tentative Topics:
Introduction: What is AI?
LISP
Uninformed Search
Informed Search
Constraint Satisfaction Problem
Game Playing
Propositional Logic
First Order Logic
Reasoning under Uncertainty
Bayesian Network
Machine Learning
Causal Inference
Homework:
There will be about 6 homework assignments during the semester as we cover the corresponding material. Homework consists of both problem solving and LISP programming.
Unless otherwise indicated, you may talk to other students about the homework problems but each student must hand in their own answers and write their own code in the programming part. You also must indicate on each homework with whom you collaborated and cite any other sources you use including Internet websites. Students should never see another student’s solution before submitting their own. Students cannot use old solution sets for this class or solution manual to the textbook under any circumstances.Homework assignments will be submitted through Canvas.
You will have a one-time exemption for a one-day late submission that you can apply to any of your assignments. This will be applied automatically at the end of the semester. The second or subsequent late assignments will be marked as 0 at the end of the semester.
Please submit your homework on time. Homework is worth full credit if submitted before the due date. After the due date, it is worth zero credit, except for the one-time exemption of a one-day late submission. No excuses will be allowed unless you provide an official doctor's note before the deadline and receive my approval.
Exam:
There will be one midterm and then a final. The exams are open book and open notes, and consist mostly of multiple-choice questions. You are not allowed to discuss them with other people. Missing any exams will automatically result in an F grade.
Tentative Midterm: Mar. 3 at HCB 0103 (In Class)
Final: Apr. 30 12:30PM-2:30PM at HCB 0103
Extra Credit:
There will be extra credit questions on midterm and final.
Academic Integrity Policy:
All students are expected to uphold the Academic Honor Code published in The Florida State University Bulletin and the Student Handbook. The Academic Honor System of The Florida State University is based on the premise that each student has the responsibility (1) to uphold the highest standards of academic integrity in the student's own work, (2) to refuse to tolerate violations of academic integrity in the university community, and (3) to foster a high sense of integrity and social responsibility on the part of the university community.
web site for a complete explanation of the Academic Honor Code.
https://fda.fsu.edu/academic-resources/academic-integrity-and-grievances/academic-honor-policy
COURSE POLICIES:
First Day Attendance Policy: Official university policy is that any student not attending the first class meeting will be automatically dropped from the class.