Cooperative solutions to exploration tasks under speed and budget constraints

Karishma and Shrisha Rao

Journal of Simulation, 2023, vol. 17, issue 6, 676-687

Abstract: We present a multi-agent system where agents can cooperate to solve a system of dependent tasks, with agents having the capability to explore a solution space and make inferences, as well as query for information under a limited budget. Re-exploration of the solution space only happens when an older solution expires. We investigate the effects of task dependencies, increasing the speed of the agents, the complexity of the problem space, and the query budgets available to agents. Specifically, we evaluate trade-offs between the agent’s speed and query budget. We observe that increasing the speed of a single agent improves the system performance to a certain point only and increasing the number of faster agents may not improve the system performance due to task dependencies. Favouring faster agents during budget allocation enhances the system performance, in line with the “Matthew effect”.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/17477778.2022.2043792 (text/html)
Access to full text is restricted to subscribers.

Related works:
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:taf:tjsmxx:v:17:y:2023:i:6:p:676-687

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjsm20

DOI: 10.1080/17477778.2022.2043792

Access Statistics for this article

Journal of Simulation is currently edited by Christine Currie

More articles in Journal of Simulation from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().