Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6863487 | Neural Networks | 2012 | 4 Pages |
Abstract
The impulsive preference of an animal for an immediate reward implies that it might subjectively discount the value of potential future outcomes. A theoretical framework to maximize the discounted subjective value has been established in the reinforcement learning theory. The framework has been successfully applied in engineering. However, this study identified a limitation when applied to animal behavior, where in some cases, there is no learning goal. Here a possible learning framework was proposed that is well-posed in any cases and that is consistent with the impulsive preference.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yoshiya Yamaguchi, Yutaka Sakai,