Learning Lyapunov-Stable Polynomial Dynamical Systems Through Imitation

Imitation learning is a paradigm to address complex motion planning problems by learning a policy to imitate an expert's behavior. However, relying solely on the expert's data might lead to unsafe actions when the robot deviates from the demonstrated trajectories. Stability guarantees have previously been provided utilizing nonlinear dynamical systems, acting as high-level motion planners, in conjunction with the Lyapunov stability theorem. Yet, these methods are prone to inaccurate policies, high computational cost, sample inefficiency, or quasi stability when replicating complex and highly nonlinear trajectories. To mitigate this problem, we present an approach for learning a globally stable nonlinear dynamical system as a motion planning policy. We model the nonlinear dynamical system as a parametric polynomial and learn the polynomial's coefficients jointly with a Lyapunov candidate. To showcase its success, we compare our method against the state of the art in simulation and conduct real-world experiments with the Kinova Gen3 Lite manipulator arm. Our experiments demonstrate the sample efficiency and reproduction accuracy of our method for various expert trajectories, while remaining stable in the face of perturbations.Comment: In 7th Annual Conference on Robot Learning 2023 Aug 3

FED-CD: Federated Causal Discovery from Interventional and Observational Data

Causal discovery, the inference of causal relations from data, is a core task of fundamental importance in all scientific domains, and several new machine learning methods for addressing the causal discovery problem have been proposed recently. However, existing machine learning methods for causal discovery typically require that the data used for inference is pooled and available in a centralized location. In many domains of high practical importance, such as in healthcare, data is only available at local data-generating entities (e.g. hospitals in the healthcare context), and cannot be shared across entities due to, among others, privacy and regulatory reasons. In this work, we address the problem of inferring causal structure - in the form of a directed acyclic graph (DAG) - from a distributed data set that contains both observational and interventional data in a privacy-preserving manner by exchanging updates instead of samples. To this end, we introduce a new federated framework, FED-CD, that enables the discovery of global causal structures both when the set of intervened covariates is the same across decentralized entities, and when the set of intervened covariates are potentially disjoint. We perform a comprehensive experimental evaluation on synthetic data that demonstrates that FED-CD enables effective aggregation of decentralized data for causal discovery without direct sample sharing, even when the contributing distributed data sets cover disjoint sets of interventions. Effective methods for causal discovery in distributed data sets could significantly advance scientific discovery and knowledge sharing in important settings, for instance, healthcare, in which sharing of data across local sites is difficult or prohibited

Chemical composition, rumen degradability and fermentation characteristics of fresh pragmates australis ensiled with different additives

Introduction: Pragmates australis (Pa) (common reed) is a riverside perennial grass found in wetlands throughout temperate and tropical regions of the world. Pa grows in many wetlands around rivers in Iran. Animal feed restriction is the main problem of Iranian animal production systems and this feed resource can be fed to native livestock especially in rural areas. Ensiling Pa could improve its feeding value. The aim of this study, therefore, was to measure the chemical composition, gas production and rumen degradability characteristics of the fresh and ensiled Pa with different additives. Materials and Methods: Plant samples were harvested during growth season from the city of Bojnoord,in Iran. The Pa samples were chopped and ensiled into airtight plastic bags as follow; 1)the fresh whole plant of Pa as control (Pa), 2) pa + 4% NaOH, 3) Pa+4% urea, 4) Pa+10% molasses, 5) Pa+4% urea +10% molasses and 6) pa+4% urea + 10% molasses +4% NaOH (on DM basis). Duration of the ensiling process lasted 60 days. Chemical composition of the samples was measured through the ordinary lab methods. The in vitro gas production was determined at 2, 4, 6, 8, 12, 24, 36, 48, 72 and 96 hrs intervals after incubation. The in situ rumen degradability was also determined at 0, 2, 4, 8, 12, 24, 36, 48, 72, 96 hrs after incubation. The experiment data were analyzed in a completely randomized design. Results and Discussion: NDF and ADF contents of the ensiled samples with urea were the highest whereas they were the lowest in the NaOH treated samples. CP content of the urea treated Pa was higher than other samples. Ash content of the NaOH treated forage was significantly (

The effect of wheat straw substitution by different levels of date palm leaves on performance and health of Baluchi ewe lamb

Introduction A major constraint of animal production in south of Iran is the lack of cheap source of roughages. Date palm leaves (DPL) is one of the most abundant agricultural by-products in south of Iran. Almost all pruned leaves are discarded in the fields, mainly for nutrients recycling and soil conservation (M. Wan Zahari, et al1999). The yearly maintenance of date palm tree produces a (around 20 kg per each tree) considerable quantities of green leaves (Bahman et al (1997); Pascual et al (2000)). Ruminant can utilize crop residues, with poor nutritional value. These residues are traditionally fed to animal as the main part of diet in many developing countries. However; dry matter intake of these by-products are not adequate to fulfill the nutrient requirements of livestock even at maintenance level (Dixon and Egan, 2002). DPL has a great potential for use as a roughage or bulk source in total mixed ration (TMR) for ruminants in dry areas. Detailed studies on fermentation characteristics and palatability of DPL silage, as well as on animal performance, have been reported by many workers (e.g. Abu Hassan and Ishida, 1991; Ishida and Abu Hassan, 1997; Oshio et al., 1999). Some researchers such as El-din and Tag-El-Din, 1996; and Bahman et al., 1997 have reported that DPL cannot be fed to animals because of low crude protein (6-7%) and high level of fibrous cell wall content low palatability and digestibility. Therefore we design one experiment that investigates possibility of using DPL without any enrichment. The objective of this trial was to study the effect of replacement DPL with wheat straw and voluntary intake, average body gain and health of Baluchi ewe lambs. Materials and Methods Twenty-four Iranian Baluchi female lambs with initial body weight (BW) of 20.48±0.5 kg and age of 130±10 days were assigned to 4 dietary treatments in a completely randomized design. Groups were balanced for weight and experimental trail lasted for 76 days. All lambs were given a TMR composed of 39% forage (alfalfa and wheat straw or DPL) and 61% concentrate. The concentrate portion (61%) was the same for all treatments, therefore the dietary treatments differed only in forage part of diet(39%) and they were 1) wheat straw (24%), 2) wheat straw (16%), DPL (8%), 3) wheat straw (8%), DPL (16%), 4) DPL (24%). The diets were fed in form of ad libitum and total mixed ration (TMR). DPL were collected in fall season (time of pruning), dried under the sun light and stored and a dry clean shed up to starting the feeding trial. DPL were chopped in particle size of 3-5cm before mixing. Approximately all diets were isocaloric and isonitrogenos. Diets were offered to the lambs twice daily in almost equal meals at 8 am and 4 pm to meet their feed requirement and fresh water was also available for sheep at all times during the trail. Results and Discussion Feeding of DPL to Baluchi sheep did not affect their health. Such results have been reported elsewhere by other workers (Osman Mahgoub, et al., 2005). Lambs fed by diet 4 had higher fibrinogen content in their blood samples than other animals in other treatments. The highest feed intake (1033 g/day) was observed in diet 4 containing 24% of DPL. In contrast the animal fed by diet 1 (24% wheat straw) had the lowest feed intake (856 g/day) among all treatments. Average body weight gain of lambs fed by diet 1 was significantly (

Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases

Simulating the spread of infectious diseases in human communities is critical for predicting the trajectory of an epidemic and verifying various policies to control the devastating impacts of the outbreak. Many existing simulators are based on compartment models that divide people into a few subsets and simulate the dynamics among those subsets using hypothesized differential equations. However, these models lack the requisite granularity to study the effect of intelligent policies that influence every individual in a particular way. In this work, we introduce a simulator software capable of modeling a population structure and controlling the disease's propagation at an individualistic level. In order to estimate the confidence of the conclusions drawn from the simulator, we employ a comprehensive probabilistic approach where the entire population is constructed as a hierarchical random variable. This approach makes the inferred conclusions more robust against sampling artifacts and gives confidence bounds for decisions based on the simulation results. To showcase potential applications, the simulator parameters are set based on the formal statistics of the COVID-19 pandemic, and the outcome of a wide range of control measures is investigated. Furthermore, the simulator is used as the environment of a reinforcement learning problem to find the optimal policies to control the pandemic. The obtained experimental results indicate the simulator's adaptability and capacity in making sound predictions and a successful policy derivation example based on real-world data. As an exemplary application, our results show that the proposed policy discovery method can lead to control measures that produce significantly fewer infected individuals in the population and protect the health system against saturation.ISSN:1553-734XISSN:1553-735

Antioxidant activity and protecting health effects of common medicinal plants

Medicinal plants are traditionally used in folk medicine as natural healing remedies with therapeutic effects such as prevention of cardiovascular diseases, inflammation disorders, or reducing the risk of cancer. In addition, pharmacological industry utilizes medicinal plants due to the presence of active chemical substances as agents for drug synthesis. They are valuable also for food and cosmetic industry as additives, due to their preservative effects because of the presence of antioxidants and antimicrobial constituents. To commonly used medicinal plants with antioxidant activity known worldwide belong plants from several families, especially Lamiaceae (rosemary, sage, oregano, marjoram, basil, thyme, mints, balm), Apiaceae (cumin, fennel, caraway), and Zingiberaceae (turmeric, ginger). The antioxidant properties of medicinal plants depend on the plant, its variety, environmental conditions, climatic and seasonal variations, geographical regions of growth, degree of ripeness, growing practices, and many other factors such as postharvest treatment and processing. In addition, composition and concentration of present antioxidants, such as phenolic compounds, are related to antioxidant effect. For appropriate determination of antioxidant capacity, the extraction technique, its conditions, solvent used, and particular assay methodology are important