Learning Probabilistic Reward Machines from Non-Markovian Stochastic Reward Processes.
Alvaro VelasquezAndre BeckusTaylor DohmenAshutosh TrivediNoah TopperGeorge K. AtiaPublished in: CoRR (2021)
Keyphrases
- reinforcement learning
- learning process
- learning automata
- partially observable environments
- inverse reinforcement learning
- learning systems
- machine learning
- learning problems
- prior knowledge
- monte carlo
- reward function
- transfer learning
- eligibility traces
- learning agent
- stochastic process
- supervised learning
- active learning
- learning algorithm