First published 9/29/2026, 4:44:15 AM · Last updated 9/29/2026, 4:44:15 AM

RETRACTED: Dynamic pricing on maximum concurrency for heterogeneous instances using hyperparameter optimization in dueling deep reinforcement learning in a multi-cloud scenario

A SAGE-published journal article on dynamic pricing and dueling deep reinforcement learning in a multi-cloud context is labeled as retracted; the source metadata names SAGE Publications and identifies the item as a journal article. The supplied source does not provide further details about reasons for or consequences of the retraction.

Categories: technology

Generated scores

Scores are based on the cited reporting and use a 1–10 scale. Read the methodology.

Confidence: 6/10How certain the assessment is based on the clarity and evidence in the cited reporting.
Geographic reach: 1/10How widely the event reaches, from a local area (1) to worldwide impact (10).
Global importance: 2/10The event's broader significance, from limited importance (1) to major global importance (10).
Impact magnitude: 2/10The scale or severity of the real-world impact, from minor (1) to extreme (10).
Positivity: 3/10How harmful or beneficial the event is, from strongly harmful (1) to strongly positive (10).
Urgency: 2/10How time-sensitive the event is, from low urgency (1) to immediate attention needed (10).

Why it matters

The retraction indicates the article should no longer be treated as part of the reliable published literature.

Sources

RETRACTED: Dynamic pricing on maximum concurrency for heterogeneous instances using hyperparameter optimization in dueling deep reinforcement learning in a multi-cloud scenario

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