第43回統計的機械学習セミナー / The 43rd Statistical Machine Learning Seminar
- Date&Time
- 2018年8月21日(火)
/ 21 August, 2018 (Tue) 16:00
- Place
- 統計数理研究所 セミナー室5 (3階, D313)
/ Seminar room 5 (3F, D313)@ The Institute of Statistical Mathematics
- Speaker
- João Pedro Pedroso (University of Porto)
- Title
- Online correlated orienteering on continuous surfaces
- Abstract
-
This work describes a problem with origins in sea exploration, though similar problems arise in other contexts. The identification of the contents of the seafloor is important in view of a possible exploitation of some of these resources. The aim of this problem is to schedule the journey of a ship for collecting information about the composition of the seafloor. We consider a bounded surface, through which some resource can be found with a given level. This "true value" is initially unknown, except for a limited number of points for which there is previous empirical information.
Optimal expedition planning involves three subproblems, each corresponding to a different phase in the process: assessment, planning and estimation.
Assessment consists of estimating the amount of information that would be conveyed by probing the surface at each point. This is done by means of an indicator function. Previous work assumed that actual information obtained by probing is not usable at the time of planning; here, we assume that after committing to probing at a certain place, the information obtained can immediately be used to change the course of the following decisions (in particular, the set of points used for building the indicator function is dynamically expanded).
Planning, the next phase in the solution process, consists of deciding on the position of points to probe until the end of the expedition; the point to probe next is the only one to which we commit. The objective is to maximize the overall informational reward obtained, taking into account that the total duration of the trip is limited to a known bound. Hence, online planning involves using the previously available points together with the points newly probed in this trip, in order to decide the location of the next point to probe --- though an estimation of the whole remaining trip is necessary for correctly taking this decision.
The third subproblem is estimation, which is related to the final aim of the problem: an estimation of the resource level available at any point on the surface, based on all the information available at the end of the trip. This is done through regression using both the initially available points and those collected during the expedition.