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

We study settings in which autonomous agents are designed to optimize a given system-level objective. In typical approaches to this problem, each agent is endowed with a decision-making rule that specifies the agent’s choice as a function of relevant information pertaining to the system’s state. The...

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Vydané v:	Dynamic games and applications Ročník 13; číslo 1; s. 187 - 207
Hlavní autori:	Brown, Philip N., Seaton, Joshua H., Marden, Jason R.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.03.2023 Springer Nature B.V
Predmet:	Communications Engineering Computer Systems Organization and Communication Networks Control algorithms Decision making Design Distance learning Economic Theory/Quantitative Economics/Mathematical Methods Economics Equilibrium Game Theory Management Science Mathematics Mathematics and Statistics Multi-agent Dynamic Decision Making and Learning Multiagent systems Networks Operations Research Optimization Redesign Social and Behav. Sciences Utility functions Distributed optimization Game theory Utility design Networked learning
ISSN:	2153-0785, 2153-0793
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