Exploiting Macro-actions and Predicting Plan Length in Planning as Satisfiability

The use of automatically learned knowledge for a planning domain can significantly improve the performance of a generic planner when solving a problem in this domain. In this work, we focus on the well-known SAT-based approach to planning and investigate two types of learned knowledge that have not been studied in this planning framework before: macro-actions and planning horizon. Macro-actions are sequences of actions that typically occur in the solution plans, while a planning horizon of a problem is the length of a (possibly optimal) plan solving it. We propose a method that uses a machine learning tool for building a predictive model of the optimal planning horizon, and variants of the well-known planner SatPlan and solver MiniSat that can exploit macro actions and learned planning horizons to improve their performance. An experimental analysis illustrates the effectiveness of the proposed techniques

Modelling soil dust aerosol in the Bodélé depression during the BoDEx campaign

We present regional model simulations of the dust emission events during the Bodélé Dust Experiment (BoDEx) that was carried out in February and March 2005 in Chad. A box model version of the dust emission model is used to test different input parameters for the emission model, and to compare the dust emissions computed with observed wind speeds to those calculated with wind speeds from the regional model simulation. While field observations indicate that dust production occurs via self-abrasion of saltating diatomite flakes in the Bodélé, the emission model based on the assumption of dust production by saltation and using observed surface wind speeds as input parameters reproduces observed dust optical thicknesses well. Although the peak wind speeds in the regional model underestimate the highest wind speeds occurring on 10–12 March 2005, the spatio-temporal evolution of the dust cloud can be reasonably well reproduced by this model. Dust aerosol interacts with solar and thermal radiation in the regional model; it is responsible for a decrease in maximum daytime temperatures by about 5 K at the beginning the dust storm on 10 March 2005. This direct radiative effect of dust aerosol accounts for about half of the measured temperature decrease compared to conditions on 8 March. Results from a global dust model suggest that the dust from the Bodélé is an important contributor to dust crossing the African Savannah region towards the Gulf of Guinea and the equatorial Atlantic, where it can contribute up to 40% to the dust optical thickness

Better parameter-free anytime search by minimizing time between solutions

This paper presents a new anytime search algorithm, any- time explicit estimation search (AEES). AEES is an anytime search algorithm which attempts to minimize the time between improvements to its incumbent solution by taking advantage of the differences between solution cost and length. We provide an argument that minimizing the time between solutions is the right thing to do for an anytime search algorithm and show that when actions have differing costs, many state-of-the-art search algorithms, including the search strategy of LAMA11 and anytime nonparametric A*, do not minimize the time between solutions. An empirical evaluation on seven domains shows that AEES often has both the shortest time between incumbent solutions and the best solution in hand for a wide variety of cutoffs

Passenger car data – a new source of real-time weather information for nowcasting, forecasting, and road safety

Presentación realizada en la 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019

Changes in social inequality with respect to health-related living conditions of 6-year-old children in East Germany after re-unification

BACKGROUND: Since Germany re-unified in 1990, substantial social and economic changes have happened in East Germany, the former socialist German Democratic Republic (GDR). The aim of this study was to investigate the influence of these socio-economic changes in East Germany on the association between social status, measured by parental educational level, and health-related living conditions of children during the ten-year period after re-unification. METHODS: In total, 25,864 6-year-old school beginner children (51.2% male and 48.8% female) participated in cross-sectional studies which have been repeated every year from 1991 to 2000 in East Germany. Parental educational level as a social indicator was the independent variable. Dependent variables included not employed parents, small living space and health-related living conditions (e. g. damp housing, single oven heating and living at busy road). The relationships were described by odds ratios using logistic regression. RESULTS: A large overall effect of parental educational level on health-related living conditions was observed. The time trends showed that the situation regarding small living space, damp housing conditions and single oven heating improved from 1991 to 2000, while regarding not employed parents (1996–2000) and living at busy road (1991–2000) did not, but even deteriorated. 6-year old children with low parental educational level, who lived at the time of re-unification, were often under damp housing conditions and with single oven heating at homes. Nevertheless, this social inequality has almost vanished ten years later. In contrast, we found an increasing gap between low and high parental educational level with respect to the proportion of parents who were not employed (22%: 4% gain), or lived under cramped housing conditions (22%: 37% reduction), or close to a busy road (7% gain: 2% reduction). CONCLUSION: The social inequalities which already existed under the socialist system in East Germany persisted in the system of social market economy between 1991 and 2000. 6-year-old children from families with the lowest social status were living under the worst domestic conditions (e. g. living at busy road, having damp housing conditions, single oven heating and small living space) and for some conditions (e. g. living at busy road and having small living space) the gap betweenlow and high social status was even bigger in 2000 than in 1991

Are German patients burdened by the practice charge for physician visits ('Praxisgebuehr')? A cross sectional analysis of socio-economic and health related factors

<p>Abstract</p> <p>Background</p> <p>In 2004, a practice charge for physician visits ('Praxisgebuehr') was implemented in the German health care system, mainly in order to reduce expenditures of sickness funds by reducing outpatient physician visits. In the statutory sickness funds, all adults now have to pay € 10 at their first physician visit in each 3 month period, except for vaccinations and preventive services. This study looks at the effect of this new patient fee on delaying or avoiding physician visits, with a special emphasis on different income groups.</p> <p>Methods</p> <p>Six representative surveys (conducted between 2004 and 2006) of the Bertelsmann Healthcare Monitor were analysed, comprising 7,769 women and men aged 18 to 79 years. The analyses are based on stratified analyses and logistic regression models, including a focus on the subgroup having a chronic disease.</p> <p>Results</p> <p>Two results can be highlighted. First, avoiding or delaying a physician visit due to this fee is seen most often among younger and healthier adults. Second, those in the lowest income group are much more affected in this way than the better of. The multivariate analysis in the subgroup of respondents having a chronic disease shows, for example, that this reaction is reported 2.45 times more often in the lowest income group than in the highest income group (95% CI: 1.90–3.15).</p> <p>Conclusion</p> <p>The analyses indicate that the effects of the practice charge differ by socio-economic group. It would be important to assess these effects in more detail, especially the effects on health care quality and health outcomes. It can be assumed, however, that avoiding or delaying physician visits jeopardizes both, and that health inequalities are increasing due to the practice charge.</p

Refining complexity analyses in planning by exploiting the exponential time hypothesis

The use of computational complexity in planning, and in AI in general, has always been a disputed topic. A major problem with ordinary worst-case analyses is that they do not provide any quantitative information: they do not tell us much about the running time of concrete algorithms, nor do they tell us much about the running time of optimal algorithms. We address problems like this by presenting results based on the exponential time hypothesis (ETH), which is a widely accepted hypothesis concerning the time complexity of 3-SAT. By using this approach, we provide, for instance, almost matching upper and lower bounds onthe time complexity of propositional planning.Funding Agencies|National Graduate School in Computer Science (CUGS), Sweden; Swedish Research Council (VR) [621-2014-4086]</p