Carnegie Mellon University
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Periodic Tapping Mechanisms of Skill Learning in a Fast-Paced Video Game

posted on 2023-07-07, 19:02 authored by Pierre GianferraraPierre Gianferrara, Shawn BettsShawn Betts, John AndersonJohn Anderson


Dataset, software, and computational models used for a project entitled "Periodic Tapping Mechanisms of Skill Learning in a Fast-Paced Video Game".

This folder includes the 3 ACT-R models that are referenced in the paper as well as all the code and data that were used to preprocess and analyze the data. We are leveraging ACT-R's periodic tapping motor extension to simulate human learning at very fast speed (<= 500 ms) in the Auto Orbit video game.

Folder organization:

1) Periodic Tapping Skill Learning - Code: This includes the ACT-R models, demographic information, Human & model measure files, and all the scripts that were used to generate the figures and statistics

2) Periodic Tapping Skill Learning - Data: This includes the game scores and event files (log files) for both humans and ACT-R models


ONR N00014-21-1-2586

AFOSR/AFRL FA9550-18-1-0251