The computational complexity of propositional STRIPS planning
Artificial Intelligence
Complexity, decidability and undecidability results for domain-independent planning
Artificial Intelligence - Special volume on planning and scheduling
Fast planning through planning graph analysis
Artificial Intelligence
The interactive museum tour-guide robot
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Control knowledge in planning: benefits and tradeoffs
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
Using temporal logics to express search control knowledge for planning
Artificial Intelligence
Proceedings of the 1999 international conference on Logic programming
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
Smodels - An Implementation of the Stable Model and Well-Founded Semantics for Normal LP
LPNMR '97 Proceedings of the 4th International Conference on Logic Programming and Nonmonotonic Reasoning
Representing Transition Systems by Logic Programs
LPNMR '99 Proceedings of the 5th International Conference on Logic Programming and Nonmonotonic Reasoning
Stable Model Semantics of Weight Constraint Rules
LPNMR '99 Proceedings of the 5th International Conference on Logic Programming and Nonmonotonic Reasoning
Open World Planning in the Situation Calculus
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Encoding Planning Problems in Nonmonotonic Logic Programs
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Extending ConGolog to Allow Partial Ordering
ATAL '99 6th International Workshop on Intelligent Agents VI, Agent Theories, Architectures, and Languages (ATAL),
Modeling and Programming Devices and Web Agents
FAABS '00 Proceedings of the First International Workshop on Formal Approaches to Agent-Based Systems-Revised Papers
TALplanner: An Empirical Investigation of a Temporal Logic-based Forward Chaining Planner
TIME '99 Proceedings of the Sixth International Workshop on Temporal Representation and Reasoning
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
SHOP: simple hierarchical ordered planner
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Reasoning about Actions in Prioritized Default Theory
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Perspectives on logic-based approaches for reasoning about actions and change
Logic programming, knowledge representation, and nonmonotonic reasoning
Synthesis from temporal specifications using preferred answer set programming
ICTCS'05 Proceedings of the 9th Italian conference on Theoretical Computer Science
Extending action language C+ by formalizing composite actions
Correct Reasoning
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In this paper we present a declarative approach to adding domain-dependent control knowledge for Answer Set Planning (ASP). Our approach allows different types of domain-dependent control knowledge such as hierarchical, temporal, or procedural knowledge to be represented and exploited in parallel, thus combining the ideas of control knowledge in HTN-planning, GOLOG-programming, and planning with temporal knowledge into ASP. To do so, we view domain-dependent control knowledge as sets of independent constraints. An advantage of this approach is that domain-dependent control knowledge can be modularly formalized and added to the planning problem as desired. We define a set of constructs for constraint representation and provide a set of domain-independent logic programming rules for checking constraint satisfaction.