Robust distributed linear programming

This paper presents a robust, distributed algorithm to solve general linear programs. The algorithm design builds on the characterization of the solutions of the linear program as saddle points of a modified Lagrangian function. We show that the resulting continuous-time saddle-point algorithm is provably correct but, in general, not distributed because of a global parameter associated with the nonsmooth exact penalty function employed to encode the inequality constraints of the linear program. This motivates the design of a discontinuous saddle-point dynamics that, while enjoying the same convergence guarantees, is fully distributed and scalable with the dimension of the solution vector. We also characterize the robustness against disturbances and link failures of the proposed dynamics. Specifically, we show that it is integral-input-to-state stable but not input-to-state stable. The latter fact is a consequence of a more general result, that we also establish, which states that no algorithmic solution for linear programming is input-to-state stable when uncertainty in the problem data affects the dynamics as a disturbance. Our results allow us to establish the resilience of the proposed distributed dynamics to disturbances of finite variation and recurrently disconnected communication among the agents. Simulations in an optimal control application illustrate the results

Exploiting Intrinsic Stochasticity of Real-Time Simulation to Facilitate Robust Reinforcement Learning for Robot Manipulation

Simulation is essential to reinforcement learning (RL) before implementation in the real world, especially for safety-critical applications like robot manipulation. Conventionally, RL agents are sensitive to the discrepancies between the simulation and the real world, known as the sim-to-real gap. The application of domain randomization, a technique used to fill this gap, is limited to the imposition of heuristic-randomized models. We investigate the properties of intrinsic stochasticity of real-time simulation (RT-IS) of off-the-shelf simulation software and its potential to improve the robustness of RL methods and the performance of domain randomization. Firstly, we conduct analytical studies to measure the correlation of RT-IS with the occupation of the computer hardware and validate its comparability with the natural stochasticity of a physical robot. Then, we apply the RT-IS feature in the training of an RL agent. The simulation and physical experiment results verify the feasibility and applicability of RT-IS to robust RL agent design for robot manipulation tasks. The RT-IS-powered robust RL agent outperforms conventional RL agents on robots with modeling uncertainties. It requires fewer heuristic randomization and achieves better generalizability than the conventional domain-randomization-powered agents. Our findings provide a new perspective on the sim-to-real problem in practical applications like robot manipulation tasks

The Criteria for Investment of Financial Institutions in the Small and Medium-Size Enterprises

Метою статті є проведення порівняльного аналізу критеріїв інвестування небанківських фінансових інститутів у малі та середні підприємства на прикладі бізнес-ангелів та венчурних фондів. У сучасних умовах функціонування малих і середніх підприємств найпопулярнішим джерелом фінансування є банки, але вони не завжди є вигідними та доступними, саме тому відбувається поширення альтернативних інструментів розвитку підприємств. Для залучення коштів фінансових посередників бізнес повинен уявляти їхні цілі та критерії прийняття рішень для того, щоб забезпечити власну відповідність їм. Постає проблема недостатнього рівня знань критеріїв міжнародних інвесторів, які можуть побудувати "фундамент" для подальшого розвитку підприємств. Аналіз 22 сайтів венчурних фондів та 30 сайтів бізнес-ангелів та синдикатів показав, що, по-перше, не всі інвестори демонстрували вимоги щодо суб’єктів фінансування; по-друге, більшість були орієнтовані саме на стартапи. У результаті було виявлено головну відмінність проаналізованих джерел: бізнес-ангели, перш за все, звертають увагу на поточні досягнення підприємства, а венчурні фонди – на галузь, в якій воно працює. Також у бізнес-ангелів було знайдено більше вимог, а, відповідно, і критеріїв, ніж у фондів.The article is aimed at carrying out a comparative analysis of the criteria of investment of non-banking financial institutions in the small and mediumsize enterprises on the example of business angels and venture funds. In the current conditions of operation of small and medium-size enterprises the popular source of financing are banks, but they are not always profitable and accessible, therefore alternative tools of development of enterprises are present. In order to attract financial intermediaries, the business must visualize their objectives and decision-making criteria in order to ensure their compliance. There is a problem of the insufficient level of knowledge as to the criteria of international investors who could build a "foundation" for further development of enterprises. The analysis of 22 venture fund websites and 30 websites of business angels and syndicates showed that, first, not all investors displayed requirements for the subjects of financing; second, most of them were focused on start-ups exclusively. As a result, the main difference of the analyzed sources has been identified: business angels, first of all, pay attention to the current achievements of enterprise, and venture funds focus on the industry in which enterprise operates. Also, the business angels are found to have more requirements, and so, accordingly, more criteria than the venture funds

Estimate of average freeze-out volume in multifragmentation events

An estimate of the average freeze-out volume for multifragmentation events is presented. Values of volumes are obtained by means of a simulation using the experimental charged product partitions measured by the 4pi multidetector INDRA for 129Xe central collisions on Sn at 32 AMeV incident energy. The input parameters of the simulation are tuned by means of the comparison between the experimental and simulated velocity (or energy) spectra of particles and fragments.Comment: To be published in Phys. Lett. B 12 pages, 5 figure

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

Robust control design for teleoperation systems with haptic feedback using neural-adaptive backstepping

Bibliography: p. 98-10

Optimal leader allocation in UAV formation pairs under no-cost switching,”

Abstract-We study the leader allocation problem in UAV formation pairs when switching the lead incurs a fuel cost. While in formation, UAVs are assumed to adhere to a notion of -cooperativeness. The problem is formulated as the combination of a non-convex and a discrete optimization problem where the leader allocations are constrained to those that induce cooperation between UAVs. A equivalent formulation of the problem allows us to express the constraint set as a family of equality and inequality constraints. By restricting our search to solutions of a specific form, we replace the non-convex problem with a convex one while preserving the optimal value of the original problem. A necessary and sufficient condition is obtained which is used to verify a solution to the discrete problem. The results are combined to design the OPTIMAL COST ALGORITHM, which efficiently solves the original problem. Our results are verified in simulation

Distributed event-triggered optimization for linear programming

Abstract-This paper considers a network of agents whose objective is for the aggregate of their states to converge to a solution of a linear program. We assume that each agent has limited information about the problem data and communicates with other agents at discrete times of its choice. Our main contribution is the development of a distributed continuous-time dynamics and a set of state-based rules, termed triggers, that an individual agent can use to determine when to broadcast its state to neighboring agents to ensure convergence. Our technical approach to the algorithm design and analysis overcomes a number of challenges, including establishing convergence in the absence of a common smooth Lyapunov function, ensuring that the triggers are detectable by agents using only local information, and accounting for the asynchronism in the state broadcasts of the agents. Simulations illustrate our results