When Big Data Fails! Relative success of adaptive agents using coarse-grained information to compete for limited resources
Physics and Society
2018-08-15 v1 Multiagent Systems
Trading and Market Microstructure
Abstract
The recent trend for acquiring big data assumes that possessing quantitatively more and qualitatively finer data necessarily provides an advantage that may be critical in competitive situations. Using a model complex adaptive system where agents compete for a limited resource using information coarse-grained to different levels, we show that agents having access to more and better data can perform worse than others in certain situations. The relation between information asymmetry and individual payoffs is seen to be complex, depending on the composition of the population of competing agents.
Keywords
Cite
@article{arxiv.1609.08746,
title = {When Big Data Fails! Relative success of adaptive agents using coarse-grained information to compete for limited resources},
author = {V. Sasidevan and Appilineni Kushal and Sitabhra Sinha},
journal= {arXiv preprint arXiv:1609.08746},
year = {2018}
}
Comments
6 pages, 4 figures + 2 pages supplementary information