Policy Gradients with Parameter-based Exploration for Control
2008
Conference Paper
ei
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in parameter space, which leads to lower variance gradient estimates than those obtained by policy gradient methods such as REINFORCE. For several complex control tasks, including robust standing with a humanoid robot, we show that our method outperforms well-known algorithms from the fields of policy gradients, finite difference methods and population based heuristics. We also provide a detailed analysis of the differences between our method and the other algorithms.
Author(s): | Sehnke, F. and Osendorfer, C. and Rückstiess, T. and Graves, A. and Peters, J. and Schmidhuber, J. |
Book Title: | ICANN 2008 |
Journal: | Artificial Neural Networks: ICANN 2008 |
Pages: | 387-396 |
Year: | 2008 |
Month: | September |
Day: | 0 |
Editors: | Kurkova-Pohlova, V. , R. Neruda, J. Koutnik |
Publisher: | Springer |
Department(s): | Empirische Inferenz |
Bibtex Type: | Conference Paper (inproceedings) |
DOI: | 10.1007/978-3-540-87536-9_40 |
Event Name: | 18th International Conference on Artificial Neural Networks |
Event Place: | Praha, Czech Republic |
Address: | Berlin, Germany |
Digital: | 0 |
Institution: | European Neural Network Society |
Language: | en |
Organization: | Max-Planck-Gesellschaft |
School: | Biologische Kybernetik |
Links: |
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BibTex @inproceedings{5169, title = {Policy Gradients with Parameter-based Exploration for Control}, author = {Sehnke, F. and Osendorfer, C. and R{\"u}ckstiess, T. and Graves, A. and Peters, J. and Schmidhuber, J.}, journal = {Artificial Neural Networks: ICANN 2008}, booktitle = {ICANN 2008}, pages = {387-396}, editors = {Kurkova-Pohlova, V. , R. Neruda, J. Koutnik}, publisher = {Springer}, organization = {Max-Planck-Gesellschaft}, institution = {European Neural Network Society}, school = {Biologische Kybernetik}, address = {Berlin, Germany}, month = sep, year = {2008}, doi = {10.1007/978-3-540-87536-9_40}, month_numeric = {9} } |