A review of reinforcement learning based hyper-heuristics
A review of reinforcement learning based hyper-heuristics
About this item
Full title
Author / Creator
Li, Cuixia , Wei, Xiang , Wang, Jing , Wang, Shuozhe and Zhang, Shuyan
Publisher
United States: PeerJ. Ltd
Journal title
Language
English
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Publication information
Publisher
United States: PeerJ. Ltd
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Scope and Contents
Contents
The reinforcement learning based hyper-heuristics (RL-HH) is a popular trend in the field of optimization. RL-HH combines the global search ability of hyper-heuristics (HH) with the learning ability of reinforcement learning (RL). This synergy allows the agent to dynamically adjust its own strategy, leading to a gradual optimization of the solution...
Alternative Titles
Full title
A review of reinforcement learning based hyper-heuristics
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_ec8a28927963440eaa8e1cb74870da02
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_ec8a28927963440eaa8e1cb74870da02
Other Identifiers
ISSN
2376-5992
E-ISSN
2376-5992
DOI
10.7717/peerj-cs.2141
