Artificial Intelligence - Special issue on knowledge representation
HTN planning: complexity and expressivity
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Constraint Processing
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
Cauldron: A Policy-Based Design Tool
POLICY '06 Proceedings of the Seventh IEEE International Workshop on Policies for Distributed Systems and Networks
Artificial Intelligence and Grids: Workflow Planning and Beyond
IEEE Intelligent Systems
Managing the life cycle of plans
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
Business-driven decision support for change management: planning and scheduling of changes
DSOM'06 Proceedings of the 17th IFIP/IEEE international conference on Distributed Systems: operations and management
A performance and usability comparison of automated planners for IT change planning
Proceedings of the 7th International Conference on Network and Services Management
Planning in the large: efficient generation of IT change plans on large infrastructures
Proceedings of the 8th International Conference on Network and Service Management
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The IT Infrastructure Library (ITIL) Is a set of best practices that are widely accepted for IT service management. Change management Is a core ITIL process that oversees the handlng of IT changes and ensures that all change requests are carefully prioritised and authorised, that business and technical impacts are understood, and that required resources are available. During this process, IT operations teams first need to understand the change requests that are generated by business and IT personnel. They must then develop and execute concrete IT change plans for each request. The increasingly large and complex IT environment (people, technology and processes) presents a number of challenges to the efficient and effective design of the ever higher volume of IT changes: Change requests can be ill-defined, company policies and best practices are not systematically captured and enforced, manually designing changes is time consuming and error-prone. To overcome these issues we propose in this paper an automated planning based approach to change design. We illustrate bow change knowledge can be represented to encode best practices and bow to refine high-level change requests into concrete plans. A prototypical implementation shows the feasibility of the approach and demonstrates the concept of a change catalogue that can be presented to business users.