An Adaptive Reinforcement Learning Approach to Policy-Driven Autonomic Management

Policies have been explored as a basis for autonomic management. In many cases, there is a need for policy-driven autonomic systems to have the ability to adapt the use of policies based, for example, on past experience, in order to deal with human error or the unpredictability in workload character...

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Bibliographische Detailangaben

Hauptverfasser:	Bahati, R.M., Bauer, M.A.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Adaptive systems Autonomic Management Computer science Conference management Humans Learning Model Adaptation Monitoring Policy-driven Management QoS Provisioning Reinforcement Learning Runtime System performance
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