This paper presents a model for dynamic adjustment of the motivation degree, using a reinforcement learning approach, in an action selection mechanism previously developed by the authors. The learning takes place in the modification of a parameter of the model of combination of internal and external stimuli. Experiments that show the claimed properties are presented, using a VR simulation developed for such purposes. The importance of adaptation by learning in action selection is also discussed.
@article{arxiv.cs/0211038,
title = {Dynamic Adjustment of the Motivation Degree in an Action Selection Mechanism},
author = {Carlos Gershenson and Pedro Pablo Gonzalez},
journal= {arXiv preprint arXiv:cs/0211038},
year = {2007}
}
Comments
7 pages, Proceedings of ISA '2000. Wollongong, Australia