Planning with an Adaptive World Model
Conference Paper, Proceedings of (NeurIPS) Neural Information Processing Systems, pp. 450 - 456, November, 1990
Abstract
We present a new connectionist planning method [TML90]. By interaction with an unknown environment, a world model is progressively constructed using gradient descent. For deriving optimal actions with respect to future reinforcement, planning is applied in two steps: an experience network 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.
BibTeX
@conference{Thrun-1990-15802,author = {Sebastian Thrun and K. Moeller and A. Linden},
title = {Planning with an Adaptive World Model},
booktitle = {Proceedings of (NeurIPS) Neural Information Processing Systems},
year = {1990},
month = {November},
editor = {D. Touretzky, R. Lippmann},
pages = {450 - 456},
publisher = {Morgan Kaufmann},
}
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