Preallocation and Planning Under Stochastic Resource Constraints


  • Frits de Nijs Delft University of Technology
  • Matthijs Spaan Delft University of Technology
  • Mathijs de Weerdt Delft University of Technology



multi-agent planning, uncertainty, stochastic constraint


Resource constraints frequently complicate multi-agent planning problems. Existing algorithms for resource-constrained, multi-agent planning problems rely on the assumption that the constraints are deterministic. However, frequently resource constraints are themselves subject to uncertainty from external influences. Uncertainty about constraints is especially challenging when agents must execute in an environment where communication is unreliable, making on-line coordination difficult. In those cases, it is a significant challenge to find coordinated allocations at plan time depending on availability at run time. To address these limitations, we propose to extend algorithms for constrained multi-agent planning problems to handle stochastic resource constraints. We show how to factorize resource limit uncertainty and use this to develop novel algorithms to plan policies for stochastic constraints. We evaluate the algorithms on a search-and-rescue problem and on a power-constrained planning domain where the resource constraints are decided by nature. We show that plans taking into account all potential realizations of the constraint obtain significantly better utility than planning for the expectation, while causing fewer constraint violations.




How to Cite

de Nijs, F., Spaan, M., & de Weerdt, M. (2018). Preallocation and Planning Under Stochastic Resource Constraints. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1).



AAAI Technical Track: Multiagent Systems