Using Taint Analysis and Reinforcement Learning (TARL) to Repair Autonomous Robot Software

It is important to be able to establish formal performance bounds for autonomous systems. However, formal verification techniques require a model of the environment in which the system operates; a challenge for autonomous systems, especially those expected to operate over longer timescales. This paper describes work in progress to automate the monitor and repair of ROS-based autonomous robot software written for an a-priori partially known and possibly incorrect environment model. A taint analysis method is used to automatically extract the data-flow sequence from input topic to publish topic, and instrument that code. A unique reinforcement learning approximation of MDP utility is calculated, an empirical and non-invasive characterization of the inherent objectives of the software designers. By comparing off-line (a-priori) utility with on-line (deployed system) utility, we show, using a small but real ROS example, that it's possible to monitor a performance criterion and relate violations of the criterion to parts of the software. The software is then patched using automated software repair techniques and evaluated against the original off-line utility.Comment: IEEE Workshop on Assured IEEE Workshop on Assured Autonomous Systems, May, 202

On the rough Gronwall lemma and its applications

We present a rough path analog of the classical Gronwall Lemma introduced recently by A. Deya, M. Gubinelli, M. Hofmanov\'a, S. Tindel in [arXiv:1604.00437] and discuss two of its applications. First, it is applied in the framework of rough path driven PDEs in order to establish energy estimates for weak solutions. Second, it is used in order to prove uniqueness for reflected rough differential equations

DEveloping a Complex Intervention for DEteriorating Patients using Theoretical Modelling (DECIDE study): study protocol

AIM: To develop a theory-based complex intervention (targeting nursing staff), to enhance enablers and overcome barriers to enacting expected behaviour when monitoring patients and responding to abnormal vital signs that signal deterioration. DESIGN: A mixed method design including structured observations on hospital wards, field notes, brief, un-recorded interviews and semi-structured interviews to inform the development of an intervention to enhance practice. METHODS: Semi-structured interviews will be conducted with nursing staff using a topic guide informed by the Theoretical Domains Framework. Semi-structured interviews will be transcribed verbatim and coded deductively into the 14 Theoretical Domains Framework domains and then inductively into 'belief statements'. Priority domains will be identified and mapped to appropriate behaviour change techniques. Intervention content and mode of delivery (how behaviour change techniques are operationalised) will be developed using nominal groups, during which participants (clinicians) will rank behaviour change techniques /mode of delivery combinations according to acceptability and feasibility. Findings will be synthesised to develop an intervention manual. DISCUSSION: Despite being a priority for clinicians, researchers and policymakers for two decades, 'sub-optimal care' of the deteriorating ward patient persists. Existing interventions have been largely educational (i.e., targeting assumed knowledge deficits) with limited evidence that they change staff behaviour. Staff behaviour when monitoring and responding to abnormal vital signs is likely influenced by a range of mediators that includes barriers and enablers. IMPACT: Systematically applying theory and evidence-based methods, will result in the specification of an intervention which is more likely to result in behaviour change and can be tested empirically in future research. This article is protected by copyright. All rights reserved

Localization Transition of Biased Random Walks on Random Networks

We study random walks on large random graphs that are biased towards a randomly chosen but fixed target node. We show that a critical bias strength b_c exists such that most walks find the target within a finite time when b>b_c. For b<b_c, a finite fraction of walks drifts off to infinity before hitting the target. The phase transition at b=b_c is second order, but finite size behavior is complex and does not obey the usual finite size scaling ansatz. By extending rigorous results for biased walks on Galton-Watson trees, we give the exact analytical value for b_c and verify it by large scale simulations.Comment: 4 pages, includes 4 figure

Standard Model Top Quark Asymmetry at the Fermilab Tevatron

Top quark pair production at proton-antiproton colliders is known to exhibit a forward-backward asymmetry due to higher-order QCD effects. We explore how this asymmetry might be studied at the Fermilab Tevatron, including how the asymmetry depends on the kinematics of extra hard partons. We consider results for top quark pair events with one and two additional hard jets. We further note that a similar asymmetry, correlated with the presence of jets, arises in specific models for parton showers in Monte Carlo simulations. We conclude that the measurement of this asymmetry at the Tevatron will be challenging, but important both for our understanding of QCD and for our efforts to model it.Comment: 26 p., 10 embedded figs., comment added, version to appear in PR

G-Brownian Motion as Rough Paths and Differential Equations Driven by G-Brownian Motion

The present paper is devoted to the study of sample paths of G-Brownian motion and stochastic differential equations (SDEs) driven by G-Brownian motion from the view of rough path theory. As the starting point, we show that quasi-surely, sample paths of G-Brownian motion can be enhanced to the second level in a canonical way so that they become geometric rough paths of roughness 2 < p < 3. This result enables us to introduce the notion of rough differential equations (RDEs) driven by G-Brownian motion in the pathwise sense under the general framework of rough paths. Next we establish the fundamental relation between SDEs and RDEs driven by G-Brownian motion. As an application, we introduce the notion of SDEs on a differentiable manifold driven by GBrownian motion and construct solutions from the RDE point of view by using pathwise localization technique. This is the starting point of introducing G-Brownian motion on a Riemannian manifold, based on the idea of Eells-Elworthy-Malliavin. The last part of this paper is devoted to such construction for a wide and interesting class of G-functions whose invariant group is the orthogonal group. We also develop the Euler-Maruyama approximation for SDEs driven by G-Brownian motion of independent interest