Fast planning through planning graph analysis
Artificial Intelligence
An action language based on causal explanation: preliminary report
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
State-space planning by integer optimization
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
Proceedings of the 1999 international conference on Logic programming
Enhancing Disjunctive Datalog by Constraints
IEEE Transactions on Knowledge and Data Engineering
Beyond the Plan-Length Criterion
ECAI '00 Proceedings of the Workshop on Local Search for Planning and Scheduling-Revised Papers
Representing Transition Systems by Logic Programs
LPNMR '99 Proceedings of the 5th International Conference on Logic Programming and Nonmonotonic Reasoning
Planning under Incomplete Knowledge
CL '00 Proceedings of the First International Conference on Computational Logic
Conformant planning via symbolic model checking
Journal of Artificial Intelligence Research
A cost-directed planner: preliminary report
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Computing preferred answer sets by meta-interpretation in Answer Set Programming
Theory and Practice of Logic Programming
The DLV system for knowledge representation and reasoning
ACM Transactions on Computational Logic (TOCL)
Issues in parallel execution of non-monotonic reasoning systems
Parallel Computing
The DLV Project: A Tour from Theory and Research to Applications and Market
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Answer set planning under action costs
Journal of Artificial Intelligence Research
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We present Kc, which extends the declarative planning language K by action costs and optimal plans that minimize overall action costs (cheapest plans). As shown, this novel language allows for expressing some nontrivial planning tasks in an elegant way. Furthermore, it flexibly allows for representing planning problems under other optimality criteria as well, such as computing "fastest" plans (with the least number of steps), and refinement combinations of cheap and fast plans. Our experience is encouraging and supports the claim that answer set planning may be a valuable approach to advanced planning systems in which intricate planning tasks can be naturally specified and effectively solved.