A probabilistic framework for resource-constrained multi-agent planning

  • Authors:

  • Nicola Muscettola;Stephen F. Smith

  • Affiliations:

  • Dipartimento di Elettronica, Politecnico di Milano, Milano, Italy;The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
  • Year:
  • 1987

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Abstract

In this paper, we consider the problem of temporally coordinating the resource demands of a set of independent agents. We assume that resources are unreliable, making it necessary to retain imprecision in the execution times assigned to specific agent operations. To this end, a probabilistic model of resource allocation is developed for use in estimating the consequences of execution intervals (representing sets of possible resource allocation decisions). This leads to a probabilistic representation of requests for resource usage for which resource congestion constraints can be defined. We consider two applications of the framework: prediction of bottleneck resources and time bound scheduling.