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Found 3 papers, 1 papers with code
What Are the Odds? Improving the foundations of Statistical Model Checking
Markov decision processes (MDPs) are a fundamental model for decision making under uncertainty.
More for Less: Safe Policy Improvement With Stronger Performance Guarantees
In an offline reinforcement learning setting, the safe policy improvement (SPI) problem aims to improve the performance of a behavior policy according to which sample data has been generated.
Strategy Synthesis in Markov Decision Processes Under Limited Sampling Access
A central task in control theory, artificial intelligence, and formal methods is to synthesize reward-maximizing strategies for agents that operate in partially unknown environments.
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