How to keep plan execution healthy ?

Developing a conflict-free plan for a multi-agent system in a complex and dynamic environment is a difficult task. Moreover, it is impossible to take into account all possible events that might occur during the execution of the plan. Unexpected events may cause a plan execution to 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. We emphasize that, in the case of bad health, the approach of correcting the plan execution should be applied before relying on the more drastic approach of replanning. 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 many unhealthy situations can be solved adequately by corrections in the plan execution instead of performing a replanning procedure.