A reinforcement strategy for least slack scheduling using BPHT

Abstract

A general approach to delayed reinforcement learning by theuse of supervised training algorithms (BPm) is used for task scheduling. T’he neural scheduler is compared with two dynamic scheduling algorithms, least-slack and earliest deadline. Simulationsandthcneuranetworksofovareis~ttcninAda95 usingthe 
DOI: 10.1145/376503.376544

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