Learning Behavior-Selection by Emotions and Cognition in a Multi-Goal Robot Task
Abstract
The existence of emotion and cognition as two interacting systems, both with important roles in decision-making, has been recently advocated by neurophysiological research (LeDoux, 1998, Damasio, 1994. Following that idea, this paper presents the ALEC agent architecture which has both emotive and cognitive learning, as well as emotive and cognitive decision-making capabilities to adapt to real-world environments. These two learning mechanisms embody very different properties which can be related to those of natural emotion and cognition systems.
Cite
Text
Gadanho. "Learning Behavior-Selection by Emotions and Cognition in a Multi-Goal Robot Task." Journal of Machine Learning Research, 2003.Markdown
[Gadanho. "Learning Behavior-Selection by Emotions and Cognition in a Multi-Goal Robot Task." Journal of Machine Learning Research, 2003.](https://mlanthology.org/jmlr/2003/gadanho2003jmlr-learning/)BibTeX
@article{gadanho2003jmlr-learning,
title = {{Learning Behavior-Selection by Emotions and Cognition in a Multi-Goal Robot Task}},
author = {Gadanho, Sandra Clara},
journal = {Journal of Machine Learning Research},
year = {2003},
pages = {385-412},
volume = {4},
url = {https://mlanthology.org/jmlr/2003/gadanho2003jmlr-learning/}
}