Learning, Diversity and Adaptation in Changing Environments: The Role of Weak Links
Daron Acemoglu,
Asuman Ozdaglar and
Sarath Pattathil
Papers from arXiv.org
Abstract:
Adaptation to dynamic conditions requires a certain degree of diversity. If all agents take the best current action, learning that the underlying state has changed and behavior should adapt will be slower. Diversity is harder to maintain when there is fast communication between agents, because they tend to find out and pursue the best action rapidly. We explore these issues using a model of (Bayesian) learning over a social network. Agents learn rapidly from and may also have incentives to coordinate with others to whom they are connected via strong links. We show, however, that when the underlying environment changes sufficiently rapidly, any network consisting of just strong links will do only a little better than random choice in the long run. In contrast, networks combining strong and weak links, whereby the latter type of links transmit information only slowly, can achieve much higher long-run average payoffs. The best social networks are those that combine a large fraction of agents into a strongly-connected component, while still maintaining a sufficient number of smaller communities that make diverse choices and communicate with this component via weak links.
Date: 2023-04
New Economics Papers: this item is included in nep-net
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://arxiv.org/pdf/2305.00474 Latest version (application/pdf)
Related works:
Working Paper: Learning, Diversity and Adaptation in Changing Environments: The Role of Weak Links (2023) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2305.00474
Access Statistics for this paper
More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().