We study countably infinite MDPs with parity objectives. Unlike in finite MDPs, optimal strategies need not exist, and may require infinite memory if they do. We provide a complete picture of the exact strategy complexity of ε-optimal strategies (and optimal strategies, where they exist) for all subclasses of parity objectives in the Mostowski hierarchy. Either MD-strategies, Markov strategies, or 1-bit Markov strategies are necessary and sufficient, depending on the number of colors, the branching degree of the MDP, and whether one considers ε-optimal or optimal strategies. In particular, 1-bit Markov strategies are necessary and sufficient for ε-optimal (resp. optimal) strategies for general parity objectives
The Transience objective is not to visit any state infinitely often. While this is not possible in f...
We study countably infinite Markov decision processes with B\"uchi objectives, which ask to visit a ...
We study Markov decision processes (MDPs) with a countably infinite number of states and transitions...
We study countably infinite MDPs with parity objectives. Unlike in finite MDPs, optimal strategies n...
We study countably infinite MDPs with parity objectives. Unlike in finite MDPs, optimal strategies n...
We study countably infinite MDPs with parity objectives, and special cases with a bounded number of ...
We study countably infinite MDPs with parity objectives, and special cases with a bounded number of ...
We study countably infinite MDPs with parity objectives, and special cases with a bounded number of ...
We study countably infinite MDPs with parity objectives, and special cases with a bounded number of ...
We study countably infinite Markov decision processes with Büchi objectives, which ask to visit a gi...
We study countably infinite Markov decision processes (MDPs) with real-valued transition rewards. Ev...
We study countably infinite Markov decision processes (MDPs) with real-valuedtransition rewards. Eve...
Markov decision processes (MDPs) are a standard model for dynamic systems that exhibit both stochast...
We study countably infinite Markov decision processes (MDPs) with real-valued transition rewards. Ev...
The Transience objective is not to visit any state infinitely often. While this is not possible in a...
The Transience objective is not to visit any state infinitely often. While this is not possible in f...
We study countably infinite Markov decision processes with B\"uchi objectives, which ask to visit a ...
We study Markov decision processes (MDPs) with a countably infinite number of states and transitions...
We study countably infinite MDPs with parity objectives. Unlike in finite MDPs, optimal strategies n...
We study countably infinite MDPs with parity objectives. Unlike in finite MDPs, optimal strategies n...
We study countably infinite MDPs with parity objectives, and special cases with a bounded number of ...
We study countably infinite MDPs with parity objectives, and special cases with a bounded number of ...
We study countably infinite MDPs with parity objectives, and special cases with a bounded number of ...
We study countably infinite MDPs with parity objectives, and special cases with a bounded number of ...
We study countably infinite Markov decision processes with Büchi objectives, which ask to visit a gi...
We study countably infinite Markov decision processes (MDPs) with real-valued transition rewards. Ev...
We study countably infinite Markov decision processes (MDPs) with real-valuedtransition rewards. Eve...
Markov decision processes (MDPs) are a standard model for dynamic systems that exhibit both stochast...
We study countably infinite Markov decision processes (MDPs) with real-valued transition rewards. Ev...
The Transience objective is not to visit any state infinitely often. While this is not possible in a...
The Transience objective is not to visit any state infinitely often. While this is not possible in f...
We study countably infinite Markov decision processes with B\"uchi objectives, which ask to visit a ...
We study Markov decision processes (MDPs) with a countably infinite number of states and transitions...