Theory of Mind: A Familiar Aspect of Humanity to Give Machines
Abstract
My research focuses on machine models of theory of mind, a set of skills that helps humans cooperate with each other. Because these skills present themselves in behavior, inference-based measurements must be carefully designed to rule out alternate hypotheses. Producing models that display these skills requires an extensive understanding of experiences and mechanisms sufficient for learning, and the models must have robust generalization to be effective in varied domains. To address these problems, I intend to evaluate computational models of ToM using a variety of tests.
Cite
Text
Michelson. "Theory of Mind: A Familiar Aspect of Humanity to Give Machines." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I13.26923Markdown
[Michelson. "Theory of Mind: A Familiar Aspect of Humanity to Give Machines." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/michelson2023aaai-theory/) doi:10.1609/AAAI.V37I13.26923BibTeX
@inproceedings{michelson2023aaai-theory,
title = {{Theory of Mind: A Familiar Aspect of Humanity to Give Machines}},
author = {Michelson, Joel},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2023},
pages = {16125-16126},
doi = {10.1609/AAAI.V37I13.26923},
url = {https://mlanthology.org/aaai/2023/michelson2023aaai-theory/}
}