Exception Handling in Workflow Management Systems
IEEE Transactions on Software Engineering - special section on current trends in exception handling—part II
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Plan evaluation with incomplete action descriptions
Eighteenth national conference on Artificial intelligence
Ad-hoc workflow: problems and solutions
DEXA '97 Proceedings of the 8th International Workshop on Database and Expert Systems Applications
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
A case-based reasoning framework for workflow model management
Data & Knowledge Engineering - Special issue: Advances in business process management
A Meta Level Architecture For Workflow Management
Journal of Integrated Design & Process Science
Leveraging Tacit Organizational Knowledge
Journal of Management Information Systems
Reviving partial order planning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
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This paper describes an approach towards workflow management based on the combination of learning and planning. Assuming that processes cannot be fully described at build-time, the approach makes use of learning techniques, namely Inductive Logic Programming (ILP), in order to discover workflow activities as planning operators. These operators will be subsequently fed to a partial-order planner in order to find the process model as a planning solution. The continuous interplay between learning, planning and execution aims at arriving at a feasible plan by successive refinement of the operators. The approach is illustrated in two simple scenarios. The paper concludes by relating the proposed approach with previous developments in this area.