Fair Robust Assignment Using Redundancy

We study the consideration of fairness in redundant assignment for multi-agent task allocation. It has recently been shown that redundant assignment of agents to tasks provides robustness to uncertainty in task performance. However, the question of how to fairly assign these redundant resources across tasks remains unaddressed. In this paper, we present a novel problem formulation for fair redundant task allocation, in which we cast it as the optimization of worst-case task costs. Solving this problem optimally is NP-hard. Therefore, we exploit properties of supermodularity to propose a polynomial-time, near-optimal solution. Our algorithm provides a solution set that is α times larger than the optimal set size in order to guarantee a solution cost at least as good as the optimal target cost. We derive the sub- optimality bound on this cardinality relaxation, α. Additionally, we demonstrate that our algorithm performs near-optimally without the cardinality relaxation. We show the algorithm in simulations of redundant assignments of robots to goal nodes on transport networks with uncertain travel times. Empirically, our algorithm outperforms benchmarks, scales to large problems, and provides improvements in both fairness and average utility.We gratefully acknowledge the support from ARL Grant DCIST CRA W911NF-17-2-0181, NSF Grant CNS-1521617, ARO Grant W911NF-13-1- 0350, ONR Grants N00014-20-1-2822 and ONR grant N00014-20-S-B001, and Qualcomm Research. The first author acknowledges support from the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1845298

Fair Robust Assignment Using Redundancy

We study the consideration of fairness in redundant assignment for multi-agent task allocation. It has recently been shown that redundant assignment of agents to tasks provides robustness to uncertainty in task performance. However, the question of how to fairly assign these redundant resources across tasks remains unaddressed. In this paper, we present a novel problem formulation for fair redundant task allocation, in which we cast it as the optimization of worst-case task costs. Solving this problem optimally is NP-hard. Therefore, we exploit properties of supermodularity to propose a polynomial-time, near-optimal solution. Our algorithm provides a solution set that is α times larger than the optimal set size in order to guarantee a solution cost at least as good as the optimal target cost. We derive the sub- optimality bound on this cardinality relaxation, α. Additionally, we demonstrate that our algorithm performs near-optimally without the cardinality relaxation. We show the algorithm in simulations of redundant assignments of robots to goal nodes on transport networks with uncertain travel times. Empirically, our algorithm outperforms benchmarks, scales to large problems, and provides improvements in both fairness and average utility.We gratefully acknowledge the support from ARL Grant DCIST CRA W911NF-17-2-0181, NSF Grant CNS-1521617, ARO Grant W911NF-13-1- 0350, ONR Grants N00014-20-1-2822 and ONR grant N00014-20-S-B001, and Qualcomm Research. The first author acknowledges support from the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1845298

Towards Optimally Efficient Field Estimation with Threshold-Based Pruning in Real Robotic Sensor Networks

The efficiency of distributed sensor networks depends on an optimal trade-off between the usage of resources and data quality. The work in this paper addresses the problem of optimizing this trade-off in a self-configured distributed robotic sensor network, with respect to a user-defined objective function. We investigate a quadtree network topology and implement a fully distributed threshold-based field estimation algorithm. Simulations with field data as well as real robot experiments are performed, validating our distributed control strategy and evaluating the threshold-based formula for real world scenarios. We propose a theoretical analysis that predicts the system’s behavior in real world case studies. The experiments and this prediction show very good correspondence, enabling the accurate employment of the objective function, optimizing the trade-off based on user needs

On the formation of Hubble flow in Little Bangs

A dynamical appearance of scaling solutions in the relativistic hydrodynamics applied to describe ultra-relativistic heavy-ion collisions is studied. We consider the boost-invariant cylindrically symmetric systems and the effects of the phase transition are taken into account by using a temperature dependent sound velocity inferred from the lattice simulations of QCD. We find that the transverse flow acquires the scaling form r/t within the short evolution times, 10 - 15 fm, only if the initial transverse flow originating from the pre-equilibrium collective behavior is present at the initial stage of the hydrodynamic evolution. The amount of such pre-equilibrium flow is correlated with the initial pressure gradient; larger gradients require smaller initial flow. The results of the numerical calculations support the phenomenological parameterizations used in the Blast-Wave, Buda-Lund, and Cracow models of the freeze-out process.Comment: 11 page

WDHA syndrome caused by pheochromocytoma: report of a case.

A case in which a pheochromocytoma secreted vasoactive intestinal peptide, causing WDHA syndrome, is reported. The patient, a 43-year-old woman, was seen because of intractable watery diarrhea, hypokalemia and weight loss. She was found to have a mass in the right adrenal area. Preoperatively, vasoactive intestinal peptide levels were elevated, and the diagnosis of WDHA syndrome was entertained. Exploratory laparotomy revealed a tumor of the right adrenal gland, measuring 15 x 15 cm, which was resected. Histologic examination revealed it to be a pheochromocytoma. Postoperatively, vasoactive intestinal peptide returned to normal. The patient had complete remission of symptoms, and has remained well since

Assembly of Configurations in a Networked Robotic System: A Case Study on a Reconfigurable Interactive Table Lamp

In the present study, we are interested in verifying how the progressive addition of constraints on communication and localization impact the performance of a swarm of small robots in shape formation tasks. Identified to be of importance in a swarm-user interaction context, the time required to construct a given spatial configuration is considered as a performance metric. The experimental work reported in this paper starts from global and synchronized localization information, shown to be successful both on a real hardware system and in simulation. In a second step, communication is constrained to a local scale, thus obliging a single designated robot to disseminate the global localization information to the other agents. The reliability of the radio communication channel and its impact upon the performance of the system are considered

Food for thought: identifying the influential factors that affect consumption of organic produce in today's youth

Purpose: This paper seeks to identify the factors that influence the perceptions and attitudes of youth towards organic products. Unlike most research that has previously examined issues concerning organic production, this paper provides a better understanding of the behavior of young consumers towards organic products, by outlining their perceptions and attitudes towards this product category. Design/methodology/approach: The research was conducted using a survey on a stratified random sample, and the data was analysed using the multivariate factor analysis. Findings: The results showed that the vast majority of young consumers identify organic food as healthy and natural, and that its higher price is a significant barrier to purchasing, along with inaccessibility and the limited options offered. The results provide valuable information for managers and decision-makers working in organic food production and sales. Originality/value: The originality of this research stems from the fact that this is the first instance in which this type of study has been performed on this specific market. It contributes to existing literature by analyzing the concept of organic food in a less developed market; exploring it through the eyes of young people as individuals who will contribute towards the future development of society; and contextualizing the topic with problems linked to obesity, the environment, and the need to support local producers. Managerial implications: The data obtained represents a meaningful contribution to the field of organic food production and sale, as obtained results can aid in the decision process regarding the implementation of the strategy for the production development and better positioning on the market. Research limitations/ further research; The study was carried out in the CEE transition country of Montenegro, with 300 young consumers. Further research is needed to validate the results through longitudinal study

Permanent matching of coupled optical bottle resonators with better than 0.16 GHz precision

The fabrication precision is one of the most critical challenges to the creation of practical photonic circuits composed of coupled high Q-factor microresonators. While very accurate transient tuning of microresonators based on local heating has been reported, the record precision of permanent resonance positioning achieved by post-processing is still within 1 and 5 GHz. Here we demonstrate two coupled bottle microresonators fabricated at the fiber surface with resonances that are matched with a better than 0.16 GHz precision. This corresponds to a better than 0.17 Å precision in the effective fiber radius variation. The achieved fabrication precision is only limited by the resolution of our optical spectrum analyzer and can be potentially improved by an order of magnitude