A robust, distributed task allocation algorithm for time-critical, multi agent systems operating in uncertain environments

The aim of this work is to produce and test a robust, distributed, multi-agent task allocation algorithm, as these are scarce and not well-documented in the literature. The vehicle used to create the robust system is the Performance Impact algorithm (PI), as it has previously shown good performance. Three different variants of PI are designed to improve its robustness, each using Monte Carlo sampling to approximate Gaussian distributions. Variant A uses the expected value of the task completion times, variant B uses the worst-case scenario metric and variant C is a hybrid that implements a combination of these. The paper shows that, in simulated trials, baseline PI does not han-dle uncertainty well; the task-allocation success rate tends to decrease linear-ly as degree of uncertainty increases. Variant B demonstrates a worse per-formance and variant A improves the failure rate only slightly. However, in comparison, the hybrid variant C exhibits a very low failure rate, even under high uncertainty. Furthermore, it demonstrates a significantly better mean ob-jective function value than the baseline.EPSR

Reliable, distributed scheduling and rescheduling for time-critical, multiagent systems

This paper addresses two main problems with many heuristic task allocation approaches – solution trapping in local minima and static structure. The existing distributed task allocation algorithm known as PI (Performance Impact) is used as the vehicle for developing solutions to these problems as it has been shown to out-perform the state-of-the-art Consensus Based Bundle Algorithm (CBBA) for time-critical problems with tight deadlines, but is both static and sub-optimal with a tendency towards trapping in local minima. The paper describes two additional modules that are easily integrated with PI. The first extends the algorithm to permit dynamic online rescheduling in real time, and the second boosts performance by introducing an additional soft max action selection procedure that increases the algorithm’s exploratory properties. The paper demonstrates the effectiveness of the dynamic rescheduling module and shows that the average time taken to perform tasks can be reduced by up to 9% when the soft max module is used. In addition, the solution of some problems that baseline PI cannot handle is enabled by the second module. These developments represent a significant advance in the state-of-the-art for multi-agent, time-critical task assignment.EPSR

A Heuristic Distributed Task Allocation Method for Multivehicle Multitask Problems and Its Application to Search and Rescue Scenario

Using distributed task allocation methods for cooperating multivehicle systems is becoming increasingly attractive. However, most effort is placed on various specific experimental work and little has been done to systematically analyze the problem of interest and the existing methods. In this paper, a general scenario description and a system configuration are first presented according to search and rescue scenario. The objective of the problem is then analyzed together with its mathematical formulation extracted from the scenario. Considering the requirement of distributed computing, this paper then proposes a novel heuristic distributed task allocation method for multivehicle multitask assignment problems. The proposed method is simple and effective. It directly aims at optimizing the mathematical objective defined for the problem. A new concept of significance is defined for every task and is measured by the contribution to the local cost generated by a vehicle, which underlies the key idea of the algorithm. The whole algorithm iterates between a task inclusion phase, and a consensus and task removal phase, running concurrently on all the vehicles where local communication exists between them. The former phase is used to include tasks into a vehicle's task list for optimizing the overall objective, while the latter is to reach consensus on the significance value of tasks for each vehicle and to remove the tasks that have been assigned to other vehicles. Numerical simulations demonstrate that the proposed method is able to provide a conflict-free solution and can achieve outstanding performance in comparison with the consensus-based bundle algorithm

Impact of carbohydrate substrate complexity on the diversity of the human colonic microbiota.

The diversity of the colonic microbial community has been linked with health in adults and diet composition is one possible determinant of diversity. We used carefully controlled conditions in vitro to determine how the complexity and multiplicity of growth substrates influence species diversity of the human colonic microbiota. In each experiment, five parallel anaerobic fermenters that received identical faecal inocula were supplied continuously with single carbohydrates (either arabinoxylan-oligosaccharides (AXOS), pectin or inulin) or with a '3-mix' of all three carbohydrates, or with a '6-mix' that additionally contained resistant starch, β-glucan and galactomannan as energy sources. Inulin supported less microbial diversity over the first 6 d than the other two single substrates or the 3- and 6-mixes, showing that substrate complexity is key to influencing microbiota diversity. The communities enriched in these fermenters did not differ greatly at the phylum and family level, but were markedly different at the species level. Certain species were promoted by single substrates, whilst others (such as Bacteroides ovatus, LEfSe P = 0.001) showed significantly greater success with the mixed substrate. The complex polysaccharides such as pectin and arabinoxylan-oligosaccharides promoted greater diversity than simple homopolymers, such as inulin. These findings suggest that dietary strategies intended to achieve health benefits by increasing gut microbiota diversity should employ complex non-digestible substrates and substrate mixtures

Addressing robustness in time-critical, distributed, task allocation algorithms.

The aim of this work is to produce and test a robustness module (ROB-M) that can be generally applied to distributed, multi-agent task allocation algorithms, as robust versions of these are scarce and not well-documented in the literature. ROB-M is developed using the Performance Impact (PI) algorithm, as this has previously shown good results in deterministic trials. Different candidate versions of the module are thus bolted on to the PI algorithm and tested using two different task allocation problems under simulated uncertain conditions, and results are compared with baseline PI. It is shown that the baseline does not handle uncertainty well; the task-allocation success rate tends to decrease linearly as degree of uncertainty increases. However, when PI is run with one of the candidate robustness modules, the failure rate becomes very low for both problems, even under high simulated uncertainty, and so its architecture is adopted for ROB-M and also applied to MIT’s baseline Consensus Based Bundle Algorithm (CBBA) to demonstrate its flexibility. Strong evidence is provided to show that ROB-M can work effectively with CBBA to improve performance under simulated uncertain conditions, as long as the deterministic versions of the problems can be solved with baseline CBBA. Furthermore, the use of ROB-M does not appear to increase mean task completion time in either algorithm, and only 100 Monte Carlo samples are required compared to 10,000 in MIT’s robust version of the CBBA algorithm. PI with ROB-M is also tested directly against MIT’s robust algorithm and demonstrates clear superiority in terms of mean numbers of solved tasks.N/

Neuropathology of childhood‐onset basal ganglia degeneration caused by mutation of VAC14

ObjectiveTo characterize the clinical features and neuropathology associated with recessive VAC14 mutations.MethodsWhole‐exome sequencing was used to identify the genetic etiology of a rapidly progressive neurological disease presenting in early childhood in two deceased siblings with distinct neuropathological features on post mortem examination.ResultsWe identified compound heterozygous variants in VAC14 in two deceased siblings with early childhood onset of severe, progressive dystonia, and neurodegeneration. Their clinical phenotype is consistent with the VAC14–related childhood‐onset, striatonigral degeneration recently described in two unrelated children. Post mortem examination demonstrated prominent vacuolation associated with degenerating neurons in the caudate nucleus, putamen, and globus pallidus, similar to previously reported ex vivo vacuoles seen in the late‐endosome/lysosome of VAC14‐deficient neurons. We identified upregulation of ubiquitinated granules within the cell cytoplasm and lysosomal‐associated membrane protein (LAMP2) around the vacuole edge to suggest a process of vacuolation of lysosomal structures associated with active autophagocytic‐associated neuronal degeneration.InterpretationOur findings reveal a distinct clinicopathological phenotype associated with recessive VAC14 mutations.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142276/1/acn3487_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142276/2/acn3487.pd

D\u27Amico Risk Stratification Correlates with Degree of Suspicion of Prostate Cancer on Multiparametric Magnetic Resonance Imaging.

PURPOSE: We determined whether there is a correlation between D\u27Amico risk stratification and the degree of suspicion of prostate cancer on multiparametric magnetic resonance imaging based on targeted biopsies done with our electromagnetically tracked magnetic resonance imaging/ultrasound fusion platform. MATERIALS AND METHODS: A total of 101 patients underwent 3 Tesla multiparametric magnetic resonance imaging of the prostate, consisting of T2, dynamic contrast enhanced, diffusion weighted and spectroscopy images in cases suspicious for or with a diagnosis of prostate cancer. All prostate magnetic resonance imaging lesions were then identified and graded by the number of positive modalities, including low-2 or fewer, moderate-3 and high-4 showing suspicion on multiparametric magnetic resonance imaging. The biopsy protocol included standard 12-core biopsy, followed by real-time magnetic resonance imaging/ultrasound fusion targeted biopsies of the suspicious magnetic resonance lesions. Cases and lesions were stratified by the D\u27Amico risk stratification. RESULTS: In this screening population 90.1% of men had a negative digital rectal examination. Mean±SD age was 62.7±8.3 years and median prostate specific antigen was 5.8 ng/ml. Of the cases 54.5% were positive for cancer on protocol biopsy. Chi-square analysis revealed a statistically significant correlation between magnetic resonance suspicion and D\u27Amico risk stratification (p CONCLUSIONS: Our data support the notion that using multiparametric magnetic resonance prostate imaging one may assess the degree of risk associated with magnetic resonance visible lesions in the prostate

Ultrahigh Energy Cosmic Rays: The state of the art before the Auger Observatory

In this review we discuss the important progress made in recent years towards understanding the experimental data on cosmic rays with energies \agt 10^{19} eV. We begin with a brief survey of the available data, including a description of the energy spectrum, mass composition, and arrival directions. At this point we also give a short overview of experimental techniques. After that, we introduce the fundamentals of acceleration and propagation in order to discuss the conjectured nearby cosmic ray sources. We then turn to theoretical notions of physics beyond the Standard Model where we consider both exotic primaries and exotic physical laws. Particular attention is given to the role that TeV-scale gravity could play in addressing the origin of the highest energy cosmic rays. In the final part of the review we discuss the potential of future cosmic ray experiments for the discovery of tiny black holes that should be produced in the Earth's atmosphere if TeV-scale gravity is realized in Nature.Comment: Final version. To be published in Int. J. Mod. Phys.

Electronic properties of bilayer and multilayer graphene

We study the effects of site dilution disorder on the electronic properties in graphene multilayers, in particular the bilayer and the infinite stack. The simplicity of the model allows for an easy implementation of the coherent potential approximation and some analytical results. Within the model we compute the self-energies, the density of states and the spectral functions. Moreover, we obtain the frequency and temperature dependence of the conductivity as well as the DC conductivity. The c-axis response is unconventional in the sense that impurities increase the response for low enough doping. We also study the problem of impurities in the biased graphene bilayer.Comment: 36 pages, 42 figures, references adde