Sequential Allocation of Sampling Budgets in Unknown Environments

Abstract

This paper presents an algorithm based on ecological models of foraging and that uses uncertainty in scientific observations made by the robot to value future actions. It is the hypothesis of this work that the foraging strategy will be an improvement over strategies based on principles from the design of experiments literature for small budget sizes. The experiment in this paper shows that for small budget sizes the new algorithm performs at least as well as other methods. However the new algorithm does not exhaust its sampling budget by default and thus needs to be modified to outperform other approaches for large sample budgets, which provides opportunity for future work in this area.