The Sea Exploration Problem Revisited

• Type: Article in International Conference Proceedings Book
• Date: 2022

Authors

Dionisio, J (Author) Other; dos Santos, D (Author) Other; Joao Pedro Pedroso (Author) FCUP

Conference proceedings International

Title: MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE (LOD 2021), PT I

Pages: 626-640

7th International Conference on Machine Learning, Optimization, and Data Science (LOD) / 1st Symposium on Artificial Intelligence and Neuroscience (ACAIN)

ELECTR NETWORK, OCT 04-08, 2021

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

CORDIS: Physical sciences > Computer science > Cybernetics > Artificial intelligence

Other information

Authenticus ID: P-00W-5K8

DOI: 10.1007/978-3-030-95467-3_45

Abstract (EN): Sea exploration is important for countries with large areas in the ocean under their control, since in the future it may be possible to exploit some of the resources in the seafloor. The sea exploration problem was presented by Pedroso et al. [13] (unpublished); we maintain most of the paper's structure, to provide the needed theoretical background and context. In the sea exploration problem, the aim is to schedule the expedition of a ship for collecting information about the resources on the seafloor. The goal is to collect data by probing on a set of carefully chosen locations, so that the information available is optimally enriched. This problem has similarities with the orienteering problem, where the aim is to plan a time-limited trip for visiting a set of vertices, collecting a prize at each of them, in such a way that the total value collected is maximum. In our problem, the score at each vertex is associated with an estimation of the level of the resource on the given surface, which is done by regression using Gaussian processes. Hence, there is a correlation among scores on the selected vertices; this is the first difference with respect to the standard orienteering problem. The second difference is the location of each vertex, which in our problem is a freely chosen point on a given surface. Results on a benchmark test set are presented and analyzed, confirming the merit of the approach proposed. In this paper, additional methods are presented, along with a small topological result and subsequent proof of the convergence of these same methods to the optimal solution, when we have instant access to the ground truth and the underlying function is piecewise continuous.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15