COURSE | TITLE | EFF YEAR | EFF TERM | DEPARTMENT | CREDIT HOURS | ||||
CS486 | ARTIFICIAL INTELLIGENCE | 2022 | 2 | Electrical Engineering and Computer Science | 3.0 (BS=0.0, ET=0.0, MA=0.0) | ||||
SCOPE | |||||||||
The course provides an introduction to the field of Artificial Intelligence (AI). Cadets will develop an appreciation for the domain of AI and an understanding of the current interest and research in the field. The historical ideas and techniques of AI and the resulting set of concepts will be covered. Classic programs will be covered as well as underlying theory. Topics include a history of computer problem solving, heuristic search techniques, knowledge representation, knowledge engineering, predicate calculus, and expert and/or rule based systems. Advanced topics that may be covered include intelligent agents, genetic algorithms, neural networks, fuzzy logic, robotics, vision, natural language processing, learning, and the programming languages of AI. The course will emphasize the practical application of artificial intelligence to industry and business as well as DoD. | |||||||||
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SPECIAL REQUIREMENTS: | |||||||||
Term project/paper; compensatory time given. |
TYPE | COURSE | EFF YEAR | EFF TERM | TRACK | RED BOOK FLG |
PRE REQUISITE | |||||
CS384 | 2019 | 2 | 1 | Y | |
EE360 | 2014 | 1 | 1 | Y | |
MA206 | 2019 | 2 | 1 | Y | |
CS384 | 2019 | 2 | 2 | Y | |
EE300 | 2011 | 1 | 2 | Y | |
MA206 | 2019 | 2 | 2 | Y | |
CS384 | 2019 | 2 | 3 | Y | |
EE360 | 2014 | 1 | 3 | Y | |
MA256 | 2019 | 2 | 3 | Y | |
CS384 | 2019 | 2 | 4 | Y | |
EE300 | 2011 | 1 | 4 | Y | |
MA256 | 2019 | 2 | 4 | Y |
AYT | #SECT/SIZE | CPBLTY | ENRLD | WAIT | SEATS | CLOSED | DETAILS | ||
2025 - 1 | 2 | 18 | 36 | 25 | 0 | 11 | N | Hours | |
2026 - 1 | 2 | 18 | 36 | 36 | 3 | 0 | N | Hours | |
2027 - 1 | 2 | 18 | 36 | 23 | 0 | 13 | N | Hours | |
2028 - 1 | 2 | 18 | 36 | 0 | 0 | 36 | N | Hours | |
COURSE | TITLE | EFF YEAR | EFF TERM | DEPARTMENT | CREDIT HOURS | ||||
CS486 | ARTIFICIAL INTELLIGENCE | 2004 | 1 | Electrical Engineering and Computer Science | 3.0 (BS=0.0, ET=0.0, MA=0.0) | ||||
SCOPE | |||||||||
The course provides an introduction to the field of Artificial Intelligence (AI). Cadets will develop an appreciation for the domain of AI and an understanding of the current interest and research in the field. The historical ideas and techniques of AI and the resulting set of concepts will be covered. Classic programs will be covered as well as underlying theory. Topics include a history of computer problem solving, heuristic search techniques, knowledge representation, knowledge engineering, predicate calculus, and expert and/or rule based systems. Advanced topics that may be covered include intelligent agents, genetic algorithms, neural networks, fuzzy logic, robotics, vision, natural language processing, learning, and the programming languages of AI. The course will emphasize the practical application of artificial intelligence to industry and business as well as DoD. | |||||||||
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SPECIAL REQUIREMENTS: | |||||||||
Term project/paper; compensatory time given. |
TYPE | COURSE | EFF YEAR | EFF TERM | TRACK | RED BOOK FLG |
PRE REQUISITE | |||||
CS384 | 1998 | 1 | 1 | Y | |
EE360 | 2005 | 1 | 1 | Y | |
CS384 | 1998 | 1 | 2 | Y | |
EE300 | 2005 | 1 | 2 | Y |
COURSE | TITLE | EFF YEAR | EFF TERM | DEPARTMENT | CREDIT HOURS | ||||
CS486 | ARTIFICIAL INTELLIGENCE | 1997 | 1 | Electrical Engineering and Computer Science | 3.0 (BS=0.0, ET=0.0, MA=0.0) | ||||
SCOPE | |||||||||
The course is a survey of artificial intelligence topics and technologies. Students in the course will develop an understanding of the broad range of disciplines associated with artificial intelligence and an appreciation for the types of problems to which AI techniques may be applied. Topics include search techniques, predicate calculus, knowledge representation, expert and knowledge based systems, machine learning, neural networks, genetic algorithms, and intelligent agents. | |||||||||
|
|||||||||
SPECIAL REQUIREMENTS: | |||||||||
Term project/paper; compensatory time given. |
TYPE | COURSE | EFF YEAR | EFF TERM | TRACK | RED BOOK FLG |
PRE REQUISITE | |||||
CS380 | 1990 | 1 | 1 | Y | |
CS385 | 1990 | 1 | 1 | Y |