CIVILEN 5390
Transcript Abbreviation:
Knowl Syst Engng
Course Description:
Overview of biologically-inspired computing paradigms including symbolic processing, artificial intelligence, expert systems, machine learning, evolutionary computing/genetic algorithms, and neurocomputing with applications in engineering.
Course Levels:
Undergraduate (1000-5000 level)
Graduate
Designation:
Elective
General Education Course
(N/A)
Cross-Listings
(N/A)
Credit Hours (Minimum if “Range”selected):
2.00
Max Credit Hours:
2.00
Select if Repeatable:
Off
Maximum Repeatable Credits
(N/A)
Total Completions Allowed
(N/A)
Allow Multiple Enrollments in Term:
No
Course Length:
14 weeks (autumn or spring)
12 weeks (summer only)
Off Campus:
Never
Campus Location:
Columbus
Instruction Modes:
In Person (75-100% campus; 0-24% online)
Prerequisites and Co-requisites:
Prereq: Grad standing, or permission of instructor.
Electronically Enforced:
No
Exclusions:
Not open to students with credit for 739.
Course Goals / Objectives:
Familiarity with several biologically-inspired computing paradigms: symbolic processing, artificial intelligence, expert systems, machine learning, evolutionary computing/genetic algorithms, and neurocomputing with applications in engineering
Exposure to engineering problems that can be addressed by each of these paradigms
Mastery of the details of one student-chosen application problem and how to address it using one of these paradigms
Check if concurrence sought:
No
Contact Hours:
| Topic | LEC | REC | LAB | LAB Inst |
|---|---|---|---|---|
| Brain and Computational Intelligence | 3.0 | 0.0 | 0.0 | 0 |
| Artificial intelligence and symbolic processing | 9.0 | 0.0 | 0.0 | 0 |
| Artificial Life: Learning Through Emergent Behavior | 3.0 | 0.0 | 0.0 | 0 |
| Neurocomputing | 9.0 | 0.0 | 0.0 | 0 |
| Evolutionary Computing and Genetic Algorithms | 9.0 | 0.0 | 0.0 | 0 |
| Machine learning | 3.0 | 0.0 | 0.0 | 0 |
| Case-Based Reasoning | 3.0 | 0.0 | 0.0 | 0 |
| Intelligent Agents | 3.0 | 0.0 | 0.0 | 0 |
| Total | 42 | 0 | 0 | 0 |
Grading Plan:
Letter Grade
Course Components:
Lecture
Grade Roster Component:
Lecture
Credit by Exam (EM):
No
Grades Breakdown:
| Aspect | Percent |
|---|---|
| Computer project | 45% |
| Term paper | 15% |
| Final exam | 40% |
Representative Textbooks and Other Course Materials:
| Title | Author | Year |
|---|---|---|
| Artificial Intelligence Illuminated | B. Coppin |
ABET-CAC Criterion 3 Outcomes
(N/A)
ABET-ETAC Criterion 3 Outcomes
(N/A)
ABET-EAC Criterion 3 Outcomes
(N/A)
Embedded Literacies Info
(N/A)
Attachments
(N/A)
Additional Notes or Comments
(N/A)