Multi-Tier Automated Planning for Adaptive Behavior


  • Daniel Ciolek Universidad Nacional de Buenos Aires
  • Nicolás D'Ippolito Universidad Nacional de Buenos Aires
  • Alberto Pozanco Universidad Carlos III de Madrid
  • Sebastian Sardiña RMIT University


A planning domain, as any model, is never “complete” and inevitably makes assumptions on the environment's dynamic. By allowing the specification of just one domain model, the knowledge engineer is only able to make one set of assumptions, and to specify a single objective-goal. Borrowing from work in Software Engineering, we propose a multi-tier framework for planning that allows the specification of different sets of assumptions, and of different corresponding objectives. The framework aims to support the synthesis of adaptive behavior so as to mitigate the intrinsic risk in any planning modeling task. After defining the multi-tier planning task and its solution concept, we show how to solve problem instances by a succinct compilation to a form of non-deterministic planning. In doing so, our technique justifies the applicability of planning with both fair and unfair actions, and the need for more efforts in developing planning systems supporting dual fairness assumptions.




How to Cite

Ciolek, D., D’Ippolito, N., Pozanco, A., & Sardiña, S. (2020). Multi-Tier Automated Planning for Adaptive Behavior. Proceedings of the International Conference on Automated Planning and Scheduling, 30(1), 66-74. Retrieved from