Responding to Illegal Activities Along the Canadian Coastlines Using Reinforcement Learning

08/05/2021
by   Mohammed Abouheaf, et al.
13

This article elaborates on how machine learning (ML) can leverage the solution of a contemporary problem related to the security of maritime domains. The worldwide “Illegal, Unreported, and Unregulated” (IUU) fishing incidents have led to serious environmental and economic consequences which involve drastic changes in our ecosystems in addition to financial losses caused by the depletion of natural resources. The Fisheries and Aquatic Department (FAD) of the United Nation's Food and Agriculture Organization (FAO) issued a report which indicated that the annual losses due to IUU fishing reached 25 Billion. This imposes negative impacts on the future-biodiversity of the marine ecosystem and domestic Gross National Product (GNP). Hence, robust interception mechanisms are increasingly needed for detecting and pursuing the unrelenting illegal fishing incidents in maritime territories. This article addresses the problem of coordinating the motion of a fleet of marine vessels (pursuers) to catch an IUU vessel while still in local waters. The problem is formulated as a pursuer-evader problem that is tackled within an ML framework. One or more pursuers, such as law enforcement vessels, intercept an evader (i.e., the illegal fishing ship) using an online reinforcement learning mechanism that is based on a value iteration process. It employs real-time navigation measurements of the evader ship as well as those of the pursuing vessels and returns back model-free interception strategies.

READ FULL TEXT

page 9

page 10

page 11

page 12

research
06/10/2020

Machine learning and control engineering: The model-free case

This paper states that Model-Free Control (MFC), which must not be confu...
research
08/05/2021

Online Model-Free Reinforcement Learning for the Automatic Control of a Flexible Wing Aircraft

The control problem of the flexible wing aircraft is challenging due to ...
research
03/15/2023

Real-Time Measurement-Driven Reinforcement Learning Control Approach for Uncertain Nonlinear Systems

The paper introduces an interactive machine learning mechanism to proces...
research
09/27/2020

Machine Learning in Event-Triggered Control: Recent Advances and Open Issues

Network Control Systems (NCSs) have attracted much interest over the pas...
research
01/25/2023

AI Tool for Exploring How Economic Activities Impact Local Ecosystems

We present an AI-based ecosystem simulator that uses three-dimensional m...
research
03/17/2023

A Policy Iteration Approach for Flock Motion Control

The flocking motion control is concerned with managing the possible conf...

Please sign up or login with your details

Forgot password? Click here to reset