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Full-Text Articles in Physical Sciences and Mathematics
Enhancing Undergraduate Ai Courses Through Machine Learning Projects, Ingrid Russell, Zdravko Markov, Todd W. Neller, Susan Coleman
Enhancing Undergraduate Ai Courses Through Machine Learning Projects, Ingrid Russell, Zdravko Markov, Todd W. Neller, Susan Coleman
Computer Science Faculty Publications
It is generally recognized that an undergraduate introductory Artificial Intelligence course is challenging to teach. This is, in part, due to the diverse and seemingly disconnected core topics that are typically covered. The paper presents work funded by the National Science Foundation to address this problem and to enhance the student learning experience in the course. Our work involves the development of an adaptable framework for the presentation of core AI topics through a unifying theme of machine learning. A suite of hands-on semester-long projects are developed, each involving the design and implementation of a learning system that enhances a …
Pigtail: A Pig Addendum, Todd W. Neller, Clifton G.M. Presser
Pigtail: A Pig Addendum, Todd W. Neller, Clifton G.M. Presser
Computer Science Faculty Publications
The object of the jeopardy dice game Pig is to be the first player to reach 100 points. Each turn, a player repeatedly rolls a die until either a 1 is rolled or the player holds and scores the sum of the rolls (i.e., the turn total). At any time during a player’s turn, the player is faced with two choices: roll or hold. If the player rolls a 1, the player scores nothing and it becomes the opponent’s turn. If the player rolls a number other than 1, the number is added to the player’s turn total …
Unifying An Introduction To Artificial Intelligence Course Through Machine Learning Laboratory Experiences, Ingrid Russell, Zdravko Markov, Todd W. Neller, Michael Georgiopoulos, Susan Coleman
Unifying An Introduction To Artificial Intelligence Course Through Machine Learning Laboratory Experiences, Ingrid Russell, Zdravko Markov, Todd W. Neller, Michael Georgiopoulos, Susan Coleman
Computer Science Faculty Publications
This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application …