Downward refinement and the efficiency of hierarchical problem solving
Artificial Intelligence
Speeding up problem solving by abstraction: a graph oriented approach
Artificial Intelligence - Special volume on empirical methods
Fast planning through planning graph analysis
Artificial Intelligence
CPlan: a constraint programming approach to planning
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
A machine program for theorem-proving
Communications of the ACM
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Planning as constraint satisfaction: solving the planning graph by compiling it into CSP
Artificial Intelligence
Disjoint pattern database heuristics
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Generating Abstraction Hierarchies: An Automated Approach to Reducing Search in Planning
Generating Abstraction Hierarchies: An Automated Approach to Reducing Search in Planning
Changes of Problem Representation: Theory and Experiments
Changes of Problem Representation: Theory and Experiments
The Quest for Efficient Boolean Satisfiability Solvers
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Human Problem Solving
Maximizing over multiple pattern databases speeds up heuristic search
Artificial Intelligence
A system simulating representation change phenomena while problem solving
Mathematics and Computers in Simulation
Learning from planner performance
Artificial Intelligence
Showing the non-existence of solutions in systems of linear Diophantine equations
Mathematics and Computers in Simulation
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
The fast downward planning system
Journal of Artificial Intelligence Research
On the use of integer programming models in AI planning
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Unifying SAT-based and graph-based planning
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Towards a practical theory of reformulation for reasoning about physical systems
Artificial Intelligence - Special volume on reformulation
Reformulating constraint satisfaction problems to improve scalability
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
An analysis of map-based abstraction and refinement
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
Solving the 24 puzzle with instance dependent pattern databases
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
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Problem solvers are computational systems which make use of different search algorithms for solving problems. Sometimes, while employing such search algorithms, problem solvers may prove to be inefficient and take too great an effort so as to showing that the problem has no solution. For such cases, in this paper we explain a technique which provides a quick proof that finding a solution is actually impossible. This technique results in reducing the number and simplifying the topology of the states which shape a problem space. Hence, we show and prove efficient new techniques intended to find such reductions which may result to be very useful for many problems.