A probabilistic framework for resource-constrained multi-agent planning
Nicola Muscettola, Stephen F. Smith · International Joint Conference on Artificial Intelligence · 1987
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.