Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-based control framework to speed up the convergence of MARL algorithms in a network of agents. Our framework defines a multi-level organizational structure for automated supervision and a communication protocol for exch...

Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision framework to speed up the convergence of MARL algorithms in a network of agents. Our framework defines a multi-level organizational structure for automated supervision and a communication protocol for exchanging informat...

Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision framework to speed up the convergence of MARL algorithms in a network of agents. The framework defines an organizational structure for automated supervision and a communication protocol for exchanging information between...

Original scientific paper Time-dependent deformations in soft rocks represent an important part of total deformations which occur after excavation of the tunnel opening. In the light of this, comprehensive laboratory uniaxial creep tests were performed on marl rock monolits. The testing used marl as a chosen representative rock samples of the group of soft rocks which exhibits creep behaviour. ...

Citation: Wiik E, Bennion H, Sayer CD, Davidson TA, Clarke SJ, McGowan S, Prentice S, Simpson GL and Stone L (2015) The coming and going of a marl lake: multi-indicator palaeolimnology reveals abrupt ecological change and alternative views of reference conditions. Front. Ecol. Evol. 3:82. doi: 10.3389/fevo.2015.00082 The coming and going of a marl lake: multi-indicator palaeolimnology reveals a...

This study concerned a stretch of 17 km of a 94-km highway alignment in Southeastern Nigeria that has a high incidence of pavement failure arising from subgrade failure. The subgrade of this section of the roadway is composed of Ekenkpon shale, New Netim marl, and Nkporo shale. Under the Unified Soil Classification System, the shales classify as OH (organic clay) and the marl classifies as MH (...

The massive size of the data in large graph processing requires distributed processing. However, conventional frameworks for distributed graph processing, such as Pregel, use programming models that are well-suited for scalability but inconvenient for programming graph algorithms. In this paper, we use Green-Marl, a Domain-Specific Language for graph analysis, to describe graph algorithms intui...

Multi-Agent Reinforcement Learning (MARL) is a widely-used technique for optimization in decentralised control problems, addressing complex challenges when several agents change actions simultaneously and without collaboration. Such challenges are exacerbated when the environment in which the agents learn is inherently non-stationary, as agents’ actions are then non-deterministic. In this paper...

The increasing use of magnetic parameters as a proxy for environmental change necessitates the understanding of processes that link magnetic properties of sediments, especially organic-rich lake sediments, and environmental change. To explore the magnetic mineralpaleoenvironment link, we have recovered a 14,000 yr mineral-magnetic record fromWhite Lake, a hardwater lake containing organicrich s...

Recent theoretical results have justified the use of potential-based reward shaping as a way to improve the performance of multi-agent reinforcement learning (MARL). However, the question remains of how to generate a useful potential function. Previous research demonstrated the use of STRIPS operator knowledge to automatically generate a potential function for single-agent reinforcement learnin...