Learning intersection-closed classes with signatures
Theoretical Computer Science
Solving quantified constraint satisfaction problems
Artificial Intelligence
Quantified Constraint Satisfaction and the Polynomially Generated Powers Property
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part II
Relatively quantified constraint satisfaction
Constraints
Existentially restricted quantified constraint satisfaction
Information and Computation
The complexity of constraint satisfaction games and QCSP
Information and Computation
Quantified constraint satisfaction problems: from relaxations to explanations
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
A quantified distributed constraint optimization problem
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Set based robust design of mechanical systems using the quantifier constraint satisfaction algorithm
Engineering Applications of Artificial Intelligence
Relaxations and explanations for quantified constraint satisfaction problems
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Collapsibility in infinite-domain quantified constraint satisfaction
CSL'06 Proceedings of the 20th international conference on Computer Science Logic
CSL'05 Proceedings of the 19th international conference on Computer Science Logic
Real-time solving of quantified CSPs based on Monte-Carlo game tree search
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Qualitative temporal and spatial reasoning revisited
CSL'07/EACSL'07 Proceedings of the 21st international conference, and Proceedings of the 16th annuall conference on Computer Science Logic
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The constraint satisfaction problem (CSP) is a framework for modelling search problems. An instance of the CSP consists of a set of variables and a set of constraints on the variables; the question is to decide whether or not there is an assignment to the variables satisfying all of the constraints. The quantified constraint satisfaction problem (QCSP) is a generalization of the CSP in which variables may be both universally and existentially quantified. The general intractability of the CSP and QCSP motivates the search for restricted cases of these problems that are polynomial-time tractable. In this dissertation, we investigate the computational complexity of cases of the QCSP where the types of constraints that may appear are restricted. One of our primary tools is the algebraic approach to studying CSP complexity, which can also be used to study QCSP complexity. We first present a pair of new QCSP tractability results; one of these tractability results is arrived at by developing a sound and complete proof system for QCSPs having a certain form. We then introduce a new concept for proving QCSP tractability results called collapsibility. The key idea behind collapsibility is that for certain cases of the QCSP, deciding an instance can be reduced to deciding an ensemble of instances, all of which have a bounded number of universally quantified variables and are derived from the original instance by “collapsing” together universally quantified variables. Collapsibility provides a uniform proof technique for deriving QCSP tractability results which we use both to give alternative proofs of the initial pair of tractability results, as well as to give further tractability results.