A challenging problem in robotics is how to control multiple robots cooperatively and safely real-world applications. Yet, developing multi-robot methods from the perspective of safe multi-agent reinforcement learning (MARL) has merely been studied. To fill this gap, study, we investigate MARL for on cooperative tasks, which each individual robot not only meet its own safety constraints while m...

analyses and thermal infrared channels 4 and 5 noaa- avhrr images. this research was carried out in lut desert located in center of sub-tropical divergence dominant in' iranian plateau. the physical and thermal properties of the various desert surfaces have been determined using correlation relationships between the desert variables including: dark sand, normal sand, marl, saline soil, soil dep...

Real-world congestion problems (e.g. traffic congestion) are typically very complex and large-scale. Multiagent reinforcement learning (MARL) is a promising candidate for dealing with this emerging complexity by providing an autonomous and distributed solution to these problems. However, there are three limiting factors that affect the deployability of MARL approaches to congestion problems. Th...

To achieve general intelligence, agents must learn how to interact with others in a shared environment: this is the challenge of multiagent reinforcement learning (MARL). The simplest form is independent reinforcement learning (InRL), where each agent treats its experience as part of its (non-stationary) environment. In this paper, we first observe that policies learned using InRL can overfit t...

Experimental verification has been the method of choice for verifying the stability of a multi-agent reinforcement learning (MARL) algorithm as the number of agents grows and theoretical analysis becomes prohibitively complex. For cooperative agents, where the ultimate goal is to optimize some global metric, the stability is usually verified by observing the evolution of the global performance ...

Much attention has been paid to differences in leaf form and composition among vegetation types, but less to the frequently substantial variation within vegetation types. We focused on the extent to which correlations between variables are the same in both succulent-poor and succulent-rich vegetation in semi-arid SE Spain. Mean foliar [N] of perennials varied among species over a 5-fold range. ...

Datasets with hundreds to tens of thousands features is the new norm. Feature selection constitutes a central problem in machine learning, where the aim is to derive a representative set of features from which to construct a classification (or prediction) model for a specific task. Our experimental study involves microarray gene expression datasets; these are high-dimensional and noisy datasets...

Many real world problems are formulated as graphs and standard graph processing algorithms are used to search solutions. Applications of graphs and related algorithms can be found in many domains. Domains vary from standard scientific applications to social media applications such as facebook. Creating and processing graphs in HPC environments adds lot of complexities. Hiding detail complexitie...

Using a pure, bacteria-free culture of Nostoc muscorum as a bioassay test organism, it was found that the water of Bass Lake, Livingston Co., Michigan, had a severe phosphate deficiency and less severe deficiencies of K, Fe, Mn, and Mg. Emission spectrographic analyses showed that the concretions had Ca as the principal constituent, Mg as the major impurity, and Fe, Si, Mn, Al, and Sr as minor ...

Virtual Instructor enabled mobile augmented reality learning (MARL) games have the potential to provide a fun and educational experience. In these types of “serious games”, learners/game players may wear a mobile headsup display that provide a rich graphical interface over the real world allowing the real world to be augmented with digital annotations including animation, graphics, text, and vi...