ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Fast planning through planning graph analysis
Artificial Intelligence
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
A logic programming approach to knowledge-state planning, II: the DLVk system
Artificial Intelligence
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
Engineering an Incremental ASP Solver
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications
Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications
Answer Set Programming for Single-Player Games in General Game Playing
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Gearing up for effective ASP planning
Correct Reasoning
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We present a prototypical system, plasp, implementing Planning by compilation to Answer Set Programming (ASP). Our approach is inspired by Planning as Satisfiability, yet it aims at keeping the actual compilation simple in favor of modeling planning techniques by meta-programming in ASP. This has several advantages. First, ASP modelings are easily modifiable and can be studied in a transparent setting. Second, we can take advantage of available ASP grounders to obtain propositional representations. Third, we can harness ASP solvers providing incremental solving mechanisms. Finally, the ASP community gains access to a wide range of planning problems, and the planning community benefits from the knowledge representation and reasoning capacities of ASP.