An Online Optimization-Based Decision Support Tool for Small Farmers in
  India: Learning in Non-stationary Environments
Tuxun Lu Aviva Prins
Crop management decision support systems are specialized tools for farmers
that reduce the riskiness of revenue streams, especially valuable for use under
the current climate changes that impact agricultural productivity.
Unfortunately, small farmers in India, who could greatly benefit from these
tools, do not have access to them. In this paper, we model an individual
greenhouse as a Markov Decision Process (MDP) and adapt Li and Li (2019)'s
Follow the Weighted Leader (FWL) online learning algorithm to offer crop
planning advice. We successfully produce utility-preserving cropping pattern
suggestions in simulations. When we compare against an offline planning
algorithm, we achieve the same cumulative revenue with greatly reduced runtime.