Artificial Intelligence and the Common Sense of Animals. Shanahan, M., Crosby, M., Beyret, B., & Cheke, L. Trends in Cognitive Sciences, 24(11):862–872, November, 2020. ![Artificial Intelligence and the Common Sense of Animals [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex The problem of common sense remains a major obstacle to progress in artificial intelligence. Here, we argue that common sense in humans is founded on a set of basic capacities that are possessed by many other animals, capacities pertaining to the understanding of objects, space, and causality. The field of animal cognition has developed numerous experimental protocols for studying these capacities and, thanks to progress in deep reinforcement learning (RL), it is now possible to apply these methods directly to evaluate RL agents in 3D environments. Besides evaluation, the animal cognition literature offers a rich source of behavioural data, which can serve as inspiration for RL tasks and curricula.
@article{shanahan_artificial_2020,
title = {Artificial {Intelligence} and the {Common} {Sense} of {Animals}},
volume = {24},
issn = {1364-6613},
url = {https://www.sciencedirect.com/science/article/pii/S1364661320302163},
doi = {10.1016/j.tics.2020.09.002},
abstract = {The problem of common sense remains a major obstacle to progress in artificial intelligence. Here, we argue that common sense in humans is founded on a set of basic capacities that are possessed by many other animals, capacities pertaining to the understanding of objects, space, and causality. The field of animal cognition has developed numerous experimental protocols for studying these capacities and, thanks to progress in deep reinforcement learning (RL), it is now possible to apply these methods directly to evaluate RL agents in 3D environments. Besides evaluation, the animal cognition literature offers a rich source of behavioural data, which can serve as inspiration for RL tasks and curricula.},
language = {en},
number = {11},
urldate = {2023-03-08},
journal = {Trends in Cognitive Sciences},
author = {Shanahan, Murray and Crosby, Matthew and Beyret, Benjamin and Cheke, Lucy},
month = nov,
year = {2020},
pages = {862--872},
}
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