Planning for conjunctive goals
Artificial Intelligence
Formalizing planning knowledge for hierarchical planning
Computational Intelligence
O-Plan: the open planning architecture
Artificial Intelligence
Task-decomposition via plan parsing
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Artificial Intelligence - Special volume on planning and scheduling
Hierarchical task network planning: formalization, analysis, and implementation
Hierarchical task network planning: formalization, analysis, and implementation
Sound and efficient closed-world reasoning for planning
Artificial Intelligence
Intelligent Tools for Planning Knowledge Base Development and Verification
EKAW '96 Proceedings of the 9th European Knowledge Acquisition Workshop on Advances in Knowledge Acquisition
An Argument for a Hybrid HTN/Operator-Based Approach to Planning
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
Challenges in bridging plan synthesis paradigms
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
IJCAI'75 Proceedings of the 4th international joint conference on Artificial intelligence - Volume 1
A critical look at critics in HTN planning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Fast planning through planning graph analysis
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Situated agents can have goals
Robotics and Autonomous Systems
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Interacting with virtual characters in interactive storytelling
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Expressivity of STRIPS-Like and HTN-Like Planning
KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
First principles planning in BDI systems
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Translating HTNs to PDDL: a small amount of domain knowledge can go a long way
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Learning probabilistic hierarchical task networks to capture user preferences
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Landmarks in Hierarchical Planning
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
A BDI agent programming language with failure handling, declarative goals, and planning
Autonomous Agents and Multi-Agent Systems
Hybrid planning using flexible strategies
KI'05 Proceedings of the 28th annual German conference on Advances in Artificial Intelligence
On the decidability of HTN planning with task insertion
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Advanced user assistance based on AI planning
Cognitive Systems Research
A hierarchical goal-based formalism and algorithm for single-agent planning
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
The GoDeL planning system: a more perfect union of domain-independent and hierarchical planning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Hierarchical task network and action-based planning approaches have traditionally been studied separately. In many domains, human expertise in the form of hierarchical reduction schemas exists, but is incomplete. In such domains, hybrid approaches that use both HTN and action-based planning techniques are needed. In this paper, we extend our previous work on refinement planning to include hierarchical planning. Specifically, we provide a generalized plan-space refinement that is capable of handling non-primitive actions. The generalization provides a principled way of handling partially hierarchical domains, while preserving systematicity, and respecting the user-intent inherent in the reduction schemas. Our general account also puts into perspective the many surface differences between the HTN and action-based planners, and could support the transfer of progress between HTN and action-based planning approaches.