Robust Networked Multiagent Optimization: Designing Agents to Repair Their Own Utility Functions

نویسندگان

چکیده

We study settings in which autonomous agents are designed to optimize a given system-level objective. In typical approaches this problem, each agent is endowed with decision-making rule that specifies the agent’s choice as function of relevant information pertaining system’s state. The choices other system comprise key component information. This paper considers scenario rules not implementable realized due discrepancies between anticipated and available agents. focus develop methods by can preserve performance guarantees these unanticipated scenarios through local independent redesigns their own rules. First, we show general impossibility result states settings, there no redesign methodologies offer any preservation guarantees, even when affected satisfy an inconsequentiality criterion. However, then objectives submodular, utility functions do exist allow nominal degrade gracefully denied That is, submodular adapt informational inconsistencies independently without incurring much loss terms performance.

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ژورنال

عنوان ژورنال: Dynamic Games and Applications

سال: 2022

ISSN: ['2153-0793', '2153-0785']

DOI: https://doi.org/10.1007/s13235-022-00469-5