Strategic Negotiations in Endogenous Network Formation

Fuente: arXiv
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Autores principales: Jalan, Akhil, Chakrabarti, Deepayan
Formato: Preprint
Publicado: 2024
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author Jalan, Akhil
Chakrabarti, Deepayan
author_facet Jalan, Akhil
Chakrabarti, Deepayan
contents In network formation games, agents form edges with each other to maximize their utility. Each agent's utility depends on its private beliefs and its edges in the network. Strategic agents can misrepresent their beliefs to get a better resulting network. Most prior works in this area consider honest agents or a single strategic agent. Instead, we propose a model where any subset of agents can be strategic. We provide an efficient algorithm for finding the set of Nash equilibria, if any exist, and certify their nonexistence otherwise. We also show that when several strategic agents are present, their utilities can increase or decrease compared to when they are all honest. Small changes in the inter-agent correlations can cause such shifts. In contrast, the simpler one-strategic-agent setting explored in the literature lacks such complex patterns. Finally, we develop an algorithm by which new agents can learn the information needed for strategic behavior. Our algorithm works even when the (unknown) strategic agents deviate from the Nash-optimal strategies. We verify these results on both simulated networks and a real-world dataset on international trade.
format Preprint
id arxiv_https___arxiv_org_abs_2402_08779
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Strategic Negotiations in Endogenous Network Formation
Jalan, Akhil
Chakrabarti, Deepayan
Optimization and Control
Computer Science and Game Theory
Multiagent Systems
In network formation games, agents form edges with each other to maximize their utility. Each agent's utility depends on its private beliefs and its edges in the network. Strategic agents can misrepresent their beliefs to get a better resulting network. Most prior works in this area consider honest agents or a single strategic agent. Instead, we propose a model where any subset of agents can be strategic. We provide an efficient algorithm for finding the set of Nash equilibria, if any exist, and certify their nonexistence otherwise. We also show that when several strategic agents are present, their utilities can increase or decrease compared to when they are all honest. Small changes in the inter-agent correlations can cause such shifts. In contrast, the simpler one-strategic-agent setting explored in the literature lacks such complex patterns. Finally, we develop an algorithm by which new agents can learn the information needed for strategic behavior. Our algorithm works even when the (unknown) strategic agents deviate from the Nash-optimal strategies. We verify these results on both simulated networks and a real-world dataset on international trade.
title Strategic Negotiations in Endogenous Network Formation
topic Optimization and Control
Computer Science and Game Theory
Multiagent Systems
url https://arxiv.org/abs/2402.08779