Organizing long-running activities with triggers and transactions
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Controlling cooperative problem solving in industrial multi-agent systems using joint intentions
Artificial Intelligence
Dynamic change within workflow systems
COCS '95 Proceedings of conference on Organizational computing systems
Collaborative plans for complex group action
Artificial Intelligence
Data & Knowledge Engineering - Special issue on ER '96
Web interface-driven cooperative exception handling in adome workflow management system
Information Systems - Special issue on the 1st web information systems engineering conference (WISE '00)
Inheritance of workflows: an approach to tackling problems related to change
Theoretical Computer Science
Mining Exception Instances to Facilitate Workflow Exception Handling
DASFAA '99 Proceedings of the Sixth International Conference on Database Systems for Advanced Applications
The RETSINA MAS Infrastructure
Autonomous Agents and Multi-Agent Systems
Knowledge sharing, coordinated exception handling, and intelligent problem solving for cross-organizational business processes
Plans as situated action: an activity theory approach to workflow systems
ECSCW'97 Proceedings of the fifth conference on European Conference on Computer-Supported Cooperative Work
Supporting effective unexpected exceptions handling in workflow management systems
Proceedings of the 2007 ACM symposium on Applied computing
Journal of Artificial Intelligence Research
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Many critical multi-agent applications require flexibility in both, individual and collective agent behavior that cannot be addressed by existing models. An example could be an agent system destined for unexpected situation handling and recovery. The paper proposes a framework to model unexpected and exceptional situations relying on goal-oriented situated planning viewpoint integrating both knowledge-based and behavior-based ideas. The paper introduces an ontology-based knowledge model, Scenario Knowledge Base framework which represents experts' knowledge about agent capabilities to act as well as a syntactic behavior patterns structure given over the set of actions the agents are capable to execute. This framework is supported by reusable software core intended for an on-line situated planning that uses the former to dynamically infer all possible courses of actions of agents of a multi-agent system to achieve ultimate goal starting from current agent states.