We present ADAM, a software system for designing and running child language learning experiments in Python. The system uses a virtual world to simulate a grounded language acquisition process in which the language learner utilizes cognitively plausible learning algorithms to form perceptual and linguistic representations of the observed world. The modular nature of ADAM makes it easy to design and test different language learning curricula as well as learning algorithms. In this report, we describe the architecture of the ADAM system in detail, and illustrate its components with examples. We provide our code.
@article{arxiv.2105.02263,
title = {ADAM: A Sandbox for Implementing Language Learning},
author = {Ryan Gabbard and Deniz Beser and Jacob Lichtefeld and Joe Cecil and Mitch Marcus and Sarah Payne and Charles Yang and Marjorie Freedman},
journal= {arXiv preprint arXiv:2105.02263},
year = {2021}
}