Towards Business Process Intelligence to Port2Port Governance Responsibility based on Learning Algorithms

Abstract

This paper provides an approach to Port2Port Business Process Intelligence (BPIs) helping decision makers in tackling constant changes in governance responsibilities. This consideration leads to the need for Port2Port technological solutions among ports and development of capabilities on sharing information, planning and execution in a collaborative way. It is offered three Port2Port BPIs: 1) Control process for greenhouse gas emissions coming from ships, 2) The process for monitoring ballast Waters, 3) Sanitation Performance Compliance under COVID19 situation. The identification and selection of learning tasks have been integrated into the conceptualisation scheme, suggesting the exploitation of Deep reinforcement Learning (RL) to capture important aspects of the real problem facing the learning agents interacting with its environment to achieve the proposed goals.