Regular Decision Processes: Modelling Dynamic Systems without Using Hidden Variables: Extended Abstrac

We describe Regular Decision Processes (RDPs) a model in between MDPs and POMDPs. Like in POMDPs, the effect of an action may depend on the entire history of actions and observations, but this dependence is restricted to regular functions only. This makes RDP a tractable, yet rich model, that does not hypothesize hidden state, and could possibly be useful for learning dynamic systems.

Authors

• Ronen I. Brafman Ben-Gurion University
• Giuseppe De Giacomo

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