Principles of artificial intelligence
Principles of artificial intelligence
Can AI planners solve practical problems?
Computational Intelligence
O-Plan: the open planning architecture
Artificial Intelligence
Using temporal logics to express search control knowledge for planning
Artificial Intelligence
SHOP: Simple Hierarchical Ordered Planner
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Unifying SAT-based and Graph-based Planning
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Extending Planning Graphs to an ADL Subset
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
IMPACTing SHOP: Putting an AI Planner Into a Multi-Agent Environment
Annals of Mathematics and Artificial Intelligence
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
Automatic composition of aggregation workflows for transportation modeling
dg.o '05 Proceedings of the 2005 national conference on Digital government research
Constraint partitioning in penalty formulations for solving temporal planning problems
Artificial Intelligence
Hierarchical planning in BDI agent programming languages: a formal approach
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
IPSS: A Hybrid Approach to Planning and Scheduling Integration
IEEE Transactions on Knowledge and Data Engineering
Domain-independent temporal planning in a planning-graph-based approach
AI Communications
Pedagogically founded courseware generation based on HTN-planning
Expert Systems with Applications: An International Journal
Achieving far transfer in an integrated cognitive architecture
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Journal of Artificial Intelligence Research
Temporal planning using subgoal partitioning and resolution in SGPlan
Journal of Artificial Intelligence Research
Adopting context awareness in service composition
Proceedings of the First Asia-Pacific Symposium on Internetware
SiN: integrating case-based reasoning with task decomposition
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Constraint partitioning in penalty formulations for solving temporal planning problems
Artificial Intelligence
One Is Not Enough: A Hybrid Approach for IT Change Planning
DSOM '09 Proceedings of the 20th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management: Integrated Management of Systems, Services, Processes and People in IT
HTN planning for Web Service composition using SHOP2
Web Semantics: Science, Services and Agents on the World Wide Web
Pedagogically founded courseware generation for web-based learning: an HTN-planning-based approach implemented in PAIGOS
HOPPER: a hierarchical planning agent for unpredictable domains
ACSC '09 Proceedings of the Thirty-Second Australasian Conference on Computer Science - Volume 91
Nondeterministic planning for generating interactive plots
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
A BDI agent programming language with failure handling, declarative goals, and planning
Autonomous Agents and Multi-Agent Systems
A hybrid deliberative layer for robotic agents: fusing DL reasoning with HTN planning in autonomous robots
A new HTN planning framework for agents in dynamic environments
CLIMA IV'04 Proceedings of the 4th international conference on Computational Logic in Multi-Agent Systems
Dynamic agent composition from semantic web services
SWDB'04 Proceedings of the Second international conference on Semantic Web and Databases
Narrative-Centered tutorial planning for inquiry-based learning environments
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
KR4HC'11 Proceedings of the 3rd international conference on Knowledge Representation for Health-Care
Adaptive military behaviour in a collaborative simulation
Proceedings of the 2008 Summer Computer Simulation Conference
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One of the more controversial recent planning algorithms is the SHOP algorithm, an HTN planning algorithm that plans for tasks in the same order that they are to be executed. SHOP can use domaindependent knowledge to generate plans very quickly, but it can be difficult to write good knowledge bases for SHOP. Our hypothesis is that this difficulty is because SHOP's total-ordering requirement for the subtasks of its methods is more restrictive than it needs to be. To examine this hypothesis, we have developed a new HTN planning algorithm called SHOP2. Like SHOP, SHOP2 is sound and complete, and it constructs plans in the same order that they will later be executed. But unlike SHOP, SHOP2 allows the subtasks of each method to be partially ordered. Our experimental results suggest that in some problem domains, the difficulty of writing SHOP knowledge bases derives from SHOP's total-ordering requirement--and that in such cases, SHOP2 can plan as efficiently as SHOP using knowledge bases simpler than those needed by SHOP.