Artificial Intelligence - Special volume on planning and scheduling
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Specifying and Enforcing Intertask Dependencies
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
Plan evaluation with incomplete action descriptions
Eighteenth national conference on Artificial intelligence
An intelligent assistant for interactive workflow composition
Proceedings of the 9th international conference on Intelligent user interfaces
Automatically Composed Workflows for Grid Environments
IEEE Intelligent Systems
Integration of biological sources: current systems and challenges ahead
ACM SIGMOD Record
Task learning by instruction in tailor
Proceedings of the 10th international conference on Intelligent user interfaces
A snapshot of public web services
ACM SIGMOD Record
The Case for Automated Planning in Autonomic Computing
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Similarity search for web services
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Managing the life cycle of plans
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
Domain independent approaches for finding diverse plans
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Learning semantic descriptions of web information sources
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Learning partially observable deterministic action models
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Flexecution, Part 2: Understanding and Supporting Flexible Execution
IEEE Intelligent Systems
Combining Domain-Independent Planning and HTN Planning: The Duet Planner
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Continual planning and acting in dynamic multiagent environments
Autonomous Agents and Multi-Agent Systems
Planning with partial preference models
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Finding and exploiting goal opportunities in real-time during plan execution
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Planning for human-robot teaming in open worlds
ACM Transactions on Intelligent Systems and Technology (TIST)
Generating diverse plans to handle unknown and partially known user preferences
Artificial Intelligence
Automatic undo for cloud management via AI planning
HotDep'12 Proceedings of the Eighth USENIX conference on Hot Topics in System Dependability
SAP speaks PDDL: exploiting a software-engineering model for planning in business process management
Journal of Artificial Intelligence Research
Refining incomplete planning domain models through plan traces
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Supporting undoability in systems operations
LISA'13 Proceedings of the 27th international conference on Large Installation System Administration
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The automated planning community has traditionally focused on the efficient synthesis of plans given a complete domain theory. In the past several years, this line of work met with significant successes, and the future course of the community seems to be set on efficient planning with even richer models. While this line of research has its applications, there are also many domains and scenarios where the first bottleneck is getting the domain model at any level of completeness. In these scenarios, the modeling burden automatically renders the planning technology unusable. To counter this, I will motivate model-lite planning technology aimed at reducing the domain-modeling burden (possibly at the expense of reduced functionality), and outline the research challenges that need to be addressed to realize it.