Markov abstractions for PAC reinforcement learning in non-Markov decision processes
Our work aims at developing reinforcement learning algorithms that do not rely on the Markov assumption. We consider the class of Non-Markov Decision Processes where histories can be abstracted into a finite set of states while preserving the dynamics. We call it a Markov abstraction since it induce...
| Main Authors: | , , |
|---|---|
| 格式: | Conference item |
| 语言: | English |
| 出版: |
International Joint Conferences on Artificial Intelligence
2022
|