None
Course Number:
CSCI 4450
Approved Starting Semester:
Fall 2025
Course Title:
Foundations of Artificial Intelligence
Course Description (Bulletin Description):
A survey of the fundamental concepts, algorithms, and data structures used to construct intelligent agents. Topics include problem solving, representing certain and uncertain knowledge, logical and probabilistic reasoning, and decision-making strategies.
Prerequisite:
CSCI 3250
Co-requisite:
None
Pre/Co-requisite::
None
Dual-Listed:
None
Course Objectives (Course-level Student Learning Outcomes):
* List the defining characteristics of an intelligent agent. * Describe the problem of combinatorial explosion of search space and its consequences. * Translate a natural language (e.g., English) sentence into a predicate logic statement. * Apply resolution to a set of logic statements to answer a query. * Compare and contrast the basic techniques for representing uncertainty. * Define the concept of a planning system and how it differs from classical search techniques. * Apply Bayes’ rule to determine the probability of a hypothesis given evidence. * Describe the complexities of temporal probabilistic reasoning. * Describe the relationship between preferences and utility functions. * Define and contrast deterministic and stochastic grammars, providing examples to show the adequacy of each. * Explain the differences among the three main styles of learning: supervised, reinforcement, and unsupervised. * Summarize the importance of image and object recognition in AI and indicate several significant applications of this technology.
Topics Covered (In Outline/Calendar):
* Intelligent agents * State-space search algorithms * Games and adversarial search * Constraint satisfaction problems * Knowledge representation and automated reasoning * Uncertainty and probabilistic reasoning * Decision-theoretic agents
Student Learning Outcomes:
- Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions. (SLO1)
- Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline. (SLO2)
- Apply computer science theory and software development fundamentals to produce computing-based solutions. (SLO6-CS)
Course Coordinator:
Dr. Nicholas Coleman
Instructor-in-charge:
Dr. Nicholas Coleman
Previous Professors:
Dr. Jiang Li, Dr. Nicholas Coleman
Technologies / Skills:
Artificial Intelligence theories
Textbook(s):
Summer/Spring 2024
Title: Artificial Intelligence, a Modern Approach
Edition: 4th
Authors: Stuart J. Russell and Peter Norvig
Publisher: Pearson
ISBN: 9780134610993
========================================
Go back to choose another course