Learning-Based Diagnosis and Repair

Nico Roos

doi:10.1007/978-3-319-76892-2_1

Learning-Based Diagnosis and Repair

Nico Roos

Robots, Agents, Interaction

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

This paper proposes a new form of diagnosis and repair based on reinforcement learning. Self-interested agents learn locally which agents may provide a low quality of service for a task. The correctness of learned assessments of other agents is proved under conditions on exploration versus exploitation of the learned assessments.

Original language	English
Pages (from-to)	1-15
Number of pages	15
Journal	Communications in Computer and Information Science
Volume	823
DOIs	https://doi.org/10.1007/978-3-319-76892-2_1
Publication status	Published - 2018

Keywords

diagnosis
multi-agent systems
reinforcement learning

Access to Document

10.1007/978-3-319-76892-2_1

Full text Final published version, 622 KBLicence: Taverne

Cite this

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