Regret Minimization in Structured Reinforcement Learning
We consider a class of sequential decision making problems in the presence of uncertainty, which belongs to the field of Reinforcement Learning (RL). Specifically, we study discrete Markov decision Processes (MDPs) which model a decision maker or agent that interacts with a stochastic and dynamic en...
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| Format: | Others |
| Language: | English |
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KTH, Reglerteknik
2021
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296238 http://nbn-resolving.de/urn:isbn:978-91-7873-839-7 |