Following the remarkable success of the AlphaGO series, 2019 was a booming year that
witnessed significant advances in multi-agent reinforcement learning (MARL) techniques …

The oil and gas industry (OGI) has always been associated with challenges and
complexities. It involves many processes and stakeholders, each generating a huge amount …

The key challenge in multiagent learning is learning a best response to the behaviour of
other agents, which may be non-stationary: if the other agents adapt their strategy as well …

This article describes a method of organizing the communication protocol, which allows
agents of the multiagent system (MAS) to make decisions about their actions. Plan activities …

Industrial Agents explains how multi-agent systems improve collaborative networks to offer
dynamic service changes, customization, improved quality and reliability, and flexible …

The digitalization of modern manufacturing systems has resulted to increasing data
generation, also known as Big Data. Although there are several technologies and …

A recent survey provides convincing evidence that JADE is among the most widely used
tools to develop agent-based software systems. It finds application in industrial settings and …

It is claimed that, in the nascent 'Cognitive Era', intelligent systems will be trained using
machine learning techniques rather than programmed by software developers. A contrary …

Multi-agent systems (MAS) have long been envisioned as a key enabling technology in
manufacturing, but this promise is yet to be realized: the lack of proper models, architectures …

Purpose Academics and practitioners have long acknowledged the potential of multiagent
systems (MAS) to automate and autonomize decision-making in logistics and supply chain …