Toward robust agent control in open environments
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
Diagnosis of single and multi-agent plans
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Using DESs for Temporal Diagnosis of Multi-agent Plan Execution
MATES '07 Proceedings of the 5th German conference on Multiagent System Technologies
Primary and secondary diagnosis of multi-agent plan execution
Autonomous Agents and Multi-Agent Systems
Diagnosis of Simple Temporal Networks
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Diagnosis of multi-agent plan execution
MATES'06 Proceedings of the 4th German conference on Multiagent System Technologies
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Unexpected events during the execution of a plan may lead to conflicts: we then say that the plan execution is unhealthy. This paper presents a new model that enables agents (1) to control plan-execution health and (2) to regain health when necessary. The agents can utilize the model to predict consequences of occurring disruptions and thus detect unhealthy situations. With the help of the model's predictions, agents can correct the execution of tasks within the plan to regain health. The applicability of the presented model is demonstrated by introducing two multi-agent protocols to keep the plan execution healthy. Finally, we investigate the solving capabilities and the efficiency of our method in experiments using randomly generated plans. Our conclusion is that a reasonable proportion of unhealthy situations can be solved adequately by corrections in the plan execution instead of performing a replanning procedure.