Consistency for quantified constraint satisfaction problems

The generalization of the constraint satisfaction problem with universal quantifiers is a challenging PSPACE-complete problem, which is interesting theoretically and also relevant to solving other PSPACE problems arising in AI, such as reasoning with uncertainty, and multiplayer games. I define two new levels of consistency for QCSP, and give an algorithm to enforce consistency for one of these definitions. The algorithm is embedded in backtracking search, and tested empirically. The aims of this work are to increase the facilities available for modelling and to increase the power of constraint propagation for QCSPs. The work is motivated by examples from adversarial games.