Partial-Observation Stochastic Games: How to Win when Belief Fails
Krishnendu Chatterjee, Laurent Doyen

TL;DR
This paper investigates strategies in two-player partial-observation stochastic games, revealing the complexity and memory requirements for winning strategies under various observation and randomization conditions.
Contribution
It provides new complexity bounds, shows belief-based strategies are insufficient in some cases, and establishes equivalences and flaws in previous results.
Findings
EXPTIME-complete decision problem for one-sided games with player 2 perfect observation
Non-elementary memory needed for one-sided games with player 1 perfect observation
Finite memory strategies suffice for two-sided games
Abstract
In two-player finite-state stochastic games of partial observation on graphs, in every state of the graph, the players simultaneously choose an action, and their joint actions determine a probability distribution over the successor states. We consider reachability objectives where player 1 tries to ensure a target state to be visited almost-surely or positively. On the basis of information, the game can be one-sided with either (a)player 1 or (b)player 2 having partial observation, or two-sided with both players having partial observation. On the basis of randomization (a)players may not be allowed to use randomization (pure strategies), or (b)may choose a probability distribution over actions but the actual random choice is not visible (actions invisible), or (c)may use full randomization. Our results for pure strategies are as follows: (1)For one-sided games with player 2 perfect…
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