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...

Full description

Saved in:

Bibliographic Details
Published in:	Dynamic games and applications Vol. 13; no. 1; pp. 187 - 207
Main Authors:	Brown, Philip N., Seaton, Joshua H., Marden, Jason R.
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.03.2023 Springer Nature B.V
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!