Planning with an Adaptive World Model
Abstract
We present a new connectionist planning method [TML90]. By interaction with an unknown environment, a world model is progressively construc(cid:173) ted using gradient descent. For deriving optimal actions with respect to future reinforcement, planning is applied in two steps: an experience net(cid:173) work proposes a plan which is subsequently optimized by gradient descent with a chain of world models, so that an optimal reinforcement may be obtained when it is actually run. The appropriateness of this method is demonstrated by a robotics application and a pole balancing task.
Cite
Text
Thrun et al. "Planning with an Adaptive World Model." Neural Information Processing Systems, 1990.Markdown
[Thrun et al. "Planning with an Adaptive World Model." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/thrun1990neurips-planning/)BibTeX
@inproceedings{thrun1990neurips-planning,
title = {{Planning with an Adaptive World Model}},
author = {Thrun, Sebastian and Möller, Knut and Linden, Alexander},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {450-456},
url = {https://mlanthology.org/neurips/1990/thrun1990neurips-planning/}
}