Specifying Non-Markovian Rewards in MDPs Using LDL on Finite Traces (Preliminary Version)

25 Jun 2017Ronen BrafmanGiuseppe De GiacomoFabio Patrizi

In Markov Decision Processes (MDPs), the reward obtained in a state depends on the properties of the last state and action. This state dependency makes it difficult to reward more interesting long-term behaviors, such as always closing a door after it has been opened, or providing coffee only following a request... (read more)

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