Structure and Problem Hardness: Goal Asymmetry and DPLL Proofs in<br> SAT-Based Planning

In Verification and in (optimal) AI Planning, a successful method is to formulate the application as boolean satisfiability (SAT), and solve it with state-of-the-art DPLL-based procedures. There is a lack of understanding of why this works so well. Focussing on the Planning context, we identify a form of problem structure concerned with the symmetrical or asymmetrical nature of the cost of achieving the individual planning goals. We quantify this sort of structure with a simple numeric parameter called AsymRatio, ranging between 0 and 1. We run experiments in 10 benchmark domains from the International Planning Competitions since 2000; we show that AsymRatio is a good indicator of SAT solver performance in 8 of these domains. We then examine carefully crafted synthetic planning domains that allow control of the amount of structure, and that are clean enough for a rigorous analysis of the combinatorial search space. The domains are parameterized by size, and by the amount of structure. The CNFs we examine are unsatisfiable, encoding one planning step less than the length of the optimal plan. We prove upper and lower bounds on the size of the best possible DPLL refutations, under different settings of the amount of structure, as a function of size. We also identify the best possible sets of branching variables (backdoors). With minimum AsymRatio, we prove exponential lower bounds, and identify minimal backdoors of size linear in the number of variables. With maximum AsymRatio, we identify logarithmic DPLL refutations (and backdoors), showing a doubly exponential gap between the two structural extreme cases. The reasons for this behavior -- the proof arguments -- illuminate the prototypical patterns of structure causing the empirical behavior observed in the competition benchmarks

PriCL: Creating a Precedent A Framework for Reasoning about Privacy Case Law

We introduce PriCL: the first framework for expressing and automatically reasoning about privacy case law by means of precedent. PriCL is parametric in an underlying logic for expressing world properties, and provides support for court decisions, their justification, the circumstances in which the justification applies as well as court hierarchies. Moreover, the framework offers a tight connection between privacy case law and the notion of norms that underlies existing rule-based privacy research. In terms of automation, we identify the major reasoning tasks for privacy cases such as deducing legal permissions or extracting norms. For solving these tasks, we provide generic algorithms that have particularly efficient realizations within an expressive underlying logic. Finally, we derive a definition of deducibility based on legal concepts and subsequently propose an equivalent characterization in terms of logic satisfiability.Comment: Extended versio

Les POMDP font de meilleurs hackers: Tenir compte de l'incertitude dans les tests de penetration

Penetration Testing is a methodology for assessing network security, by generating and executing possible hacking attacks. Doing so automatically allows for regular and systematic testing. A key question is how to generate the attacks. This is naturally formulated as planning under uncertainty, i.e., under incomplete knowledge about the network configuration. Previous work uses classical planning, and requires costly pre-processes reducing this uncertainty by extensive application of scanning methods. By contrast, we herein model the attack planning problem in terms of partially observable Markov decision processes (POMDP). This allows to reason about the knowledge available, and to intelligently employ scanning actions as part of the attack. As one would expect, this accurate solution does not scale. We devise a method that relies on POMDPs to find good attacks on individual machines, which are then composed into an attack on the network as a whole. This decomposition exploits network structure to the extent possible, making targeted approximations (only) where needed. Evaluating this method on a suitably adapted industrial test suite, we demonstrate its effectiveness in both runtime and solution quality.Comment: JFPDA 2012 (7\`emes Journ\'ees Francophones Planification, D\'ecision, et Apprentissage pour la conduite de syst\`emes), Nancy, Franc

Self-diffusion and Cooperative Diffusion in Semidilute Polymer Solutions as measured by Fluorescence Correlation Spectroscopy

We present a comprehensive investigation of polymer diffusion in the semidilute regime by fluorescence correlation spectroscopy (FCS) and dynamic light scattering (DLS). Using single-labeled polystyrene chains, FCS leads to the self-diffusion coefficient while DLS gives the cooperative diffusion coefficient for exactly the same molecular weights and concentrations. Using FCS we observe a new fast mode in the semidilute entangled concentration regime beyond the slower mode which is due to self-diffusion. Comparison of FCS data with data obtained by DLS on the same polymers shows that the second mode observed in FCS is identical to the cooperative diffusion coefficient measured with DLS. An in-depth analysis and a comparison with current theoretical models demonstrates that the new cooperative mode observed in FCS is due to the effective long-range interaction of the chains through the transient entanglement network

Detecting regulatory compliance for business process models through semantic annotations

A given business process may face a large number of regulatory obligations the process may or comply with. Providing tools and techniques through which an evaluation of the compliance degree of a given process can be undertaken is seen as a key objective in emerging business process platforms. We address this problem through a diagnostic framework that provides the ability to assess the compliance gaps present in a given process. Checking whether a process is compliant with the rules involves enumerating all reachable states and is hence, in general, a hard search problem. The approach taken here allows to provide useful diagnostic information in polynomial time. The approach is based on two underlying techniques. A conceptually faithful representation for regulatory obligations is firstly provided by a formal rule language based on a non-monotonic deontic logic of violations. Secondly, processes are formalized through semantic annotations that allow a logical state space to be created. The intersection of the two allows us to devise an efficient method to detect compliance gaps; the method guarantees to detect all obligations that will necessarily arise during execution, but that will not necessarily be fulfilled

Individual fates of mesenchymal stem cells in vitro

<p>Abstract</p> <p>Background</p> <p><it>In vitro </it>cultivated stem cell populations are in general heterogeneous with respect to their expression of differentiation markers. In hematopoietic progenitor populations, this heterogeneity has been shown to regenerate within days from isolated subpopulations defined by high or low marker expression. This kind of plasticity has been suggested to be a fundamental feature of mesenchymal stem cells (MSCs) as well. Here, we study MSC plasticity on the level of individual cells applying a multi-scale computer model that is based on the concept of noise-driven stem cell differentiation.</p> <p>Results</p> <p>By simulation studies, we provide detailed insight into the kinetics of MSC organisation. Monitoring the fates of individual cells in high and low oxygen culture, we calculated the average transition times of individual cells into stem cell and differentiated states. We predict that at low oxygen the heterogeneity of a MSC population with respect to differentiation regenerates from any selected subpopulation in about two days. At high oxygen, regeneration becomes substantially slowed down. Simulation results on the composition of the functional stem cell pool of MSC populations suggest that most of the cells that constitute this pool originate from more differentiated cells.</p> <p>Conclusions</p> <p>Individual cell-based models are well-suited to provide quantitative predictions on essential features of the spatio-temporal organisation of MSC <it>in vitro</it>. Our predictions on MSC plasticity and its dependence on the environment motivate a number of <it>in vitro </it>experiments for validation. They may contribute to a better understanding of MSC organisation <it>in vitro</it>, including features of clonal expansion, environmental adaptation and stem cell ageing.</p

SAP Speaks PDDL

International audienceIn several application areas for Planning, in particular helping with the creation of new processes in Business Process Management (BPM), a major obstacle lies in the modeling. Obtaining a suitable model to plan with is often prohibitively complicated and/or costly. Our core observation in this work is that, for software-architectural purposes, SAP is already using a model that is essentially a variant of PDDL. That model describes the behavior of Business Objects, in terms of status variables and how they are affected by system transactions. We show herein that one can leverage the model to obtain (a) a promising BPM planning application which incurs hardly any modeling costs, and (b) an interesting planning benchmark. We design a suitable planning formalism and an adaptation of FF, and we perform large-scale experiments. Our prototype is part of a research extension to the SAP NetWeaver platform