Model AI Assignments 2019

Neller, Todd W.; Sooriamurthi, Raja; Guerzhoy, Michael; Zhang, Lisa; Talaga, Paul; Archibald, Christopher; Summerville, Adam; Osborn, Joseph C.; Resnick, Cinjon; Oliver, Avital; Bhupatiraju, Surya; Agrawal, Kumar Krishna; Derbinsky, Nate; Strange, E. H.; Neumann, Marion; Chen, Jonathan; Christensen, Zac; Wollowski, Michael; Youngquist, Oscar

doi:10.1609/aaai.v33i01.33019751

Cited by 3 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Besides providing students a familiar document environment for their work, notebook style lectures and assignments encourage students to practice and utilize literate programming in the form of active note-taking and course documentation creation. We share our resources with the AI community-as others have done: (Neller et al 2019;Sintov et al 2016;Wollowski et al 2016)-and will continue to report on our trials and errors with the serverless, cloud-based, machine learning course at Fashion Institute of Technology serving non-traditional students with little to no technical backgrounds. We hope to see more discussion surrounding such curriculum adoption within higher education and encourage collaboration among institutions.…”

Section: Discussionmentioning

confidence: 97%

Using Cloud Tools for Literate Programming to Redesign an AI Course for Non-Traditional College Students

Hwang

Williamson

2020

AAAI

View full text Add to dashboard Cite

As more open source educational software applications become available, higher educational institutions have the opportunity to utilize these cost efficient tools to deliver the instruction traditionally taught off line with heavy associated costs. Here we introduce a machine learning course that uses a simple, cloud computing approach to creating course materials. We see this type of serverless, cloud-based, literate programming to be the future of computer science education in non-traditional higher educational institutions in particular serving students who will need the basic literacy for computing and computation but will not pursue the traditional computer scientist path.

show abstract

Section: Discussionmentioning

confidence: 97%

Using Cloud Tools for Literate Programming to Redesign an AI Course for Non-Traditional College Students

Hwang

Williamson

2020

AAAI

View full text Add to dashboard Cite

show abstract

“…They assessed the impact of tree size on win rate for a random-rollout player, and the impact of heuristic vs random rollout on win rate given a maximum tree size (with and without a time bound). Ultimate TicTacToe is also sometimes used in AI courses that do not have a games focus (Neller et al 2019).…”

Section: Programming Assignmentsmentioning

confidence: 99%

Teaching Game AI as an Undergraduate Course in Computational Media

Smith

2020

AAAI

View full text Add to dashboard Cite

We need to teach AI to students in and outside of traditional computer science degree programs, including those designer-engineer hybrid students who will design and implement games or engage in technical games research later. The need to rethink AI curriculum is pressing in a design education context because AI powers many emerging practical techniques such as drama management, procedural content generation, player modeling, and machine playtesting. In this paper, we describe a 5-year experimental effort to teach a Game AI course structured around a broad and expanding set of roles AI can play in game design (e.g., Adversary and Actor, as well as Design Assistant and Storyteller). This course sets up computer science and computer game design students to transform practices in the game industry as well as create new forms of media that were previously unreachable. Our students gained mastery over the relevant techniques and further demonstrated (via novel prototype systems) many new roles for AI along the way.

show abstract