Automated Design of Elevator Systems: Experimenting with Constraint-Based Approaches

System configuration and design is a well-established topic in AI. While many successful applications exists, there are still areas of manufacturing where AI techniques find little or no application. We focus on one such area, namely building and installation of elevator systems, for which we are developing an automated design and configuration tool. The questions that we address in this paper are: (i) What are the best ways to encode some subtasks of elevator design into constraint-based representations? (ii) What are the best tools available to solve the encodings? We contribute an empirical analysis to address these questions in our domain of interest, as well as the complete set of benchmarks to foster further researc

Clause/Term Resolution and Learning in the Evaluation of Quantified Boolean Formulas

Resolution is the rule of inference at the basis of most procedures for automated reasoning. In these procedures, the input formula is first translated into an equisatisfiable formula in conjunctive normal form (CNF) and then represented as a set of clauses. Deduction starts by inferring new clauses by resolution, and goes on until the empty clause is generated or satisfiability of the set of clauses is proven, e.g., because no new clauses can be generated. In this paper, we restrict our attention to the problem of evaluating Quantified Boolean Formulas (QBFs). In this setting, the above outlined deduction process is known to be sound and complete if given a formula in CNF and if a form of resolution, called Q-resolution, is used. We introduce Q-resolution on terms, to be used for formulas in disjunctive normal form. We show that the computation performed by most of the available procedures for QBFs --based on the Davis-Logemann-Loveland procedure (DLL) for propositional satisfiability-- corresponds to a tree in which Q-resolution on terms and clauses alternate. This poses the theoretical bases for the introduction of learning, corresponding to recording Q-resolution formulas associated with the nodes of the tree. We discuss the problems related to the introduction of learning in DLL based procedures, and present solutions extending state-of-the-art proposals coming from the literature on propositional satisfiability. Finally, we show that our DLL based solver extended with learning, performs significantly better on benchmarks used in the 2003 QBF solvers comparative evaluation

Conditional behavior trees: Definition, executability, and applications

Behavior Trees (BTs) are gaining acceptance in robotics to specify action policies at the deliberative level. Their advantages include modularity, ease of use and increasing tool support. In this paper, we define Conditional Behavior Trees (CBTs) as an extension of BTs wherein actions are decorated considering pre-and post-conditions. CBTs improve on basic BTs in that they enable monitoring the execution of single actions by checking pre-and post-conditions, respectively. Since there might exist action sequences wherein some preconditions are violated, CBT executability may depend on the success/failure of specific actions. We developed an encoding of CBT executability into satisfiability of propositional formulas to be checked off-line in a publicly-available tool that computes the encoding for generic CBTs. For the kind of application scenarios and related behavior specifications that we consider, we show that our approach is effective and yields formal guarantees about the executability of deliberative policies designed as CBTs

Property specification patterns at work: verification and inconsistency explanation

Property specification patterns (PSPs) have been proposed to ease the formalization of requirements, yet enable automated verification thereof. In particular, the internal consistency of specifications written with PSPs can be checked automatically with the use of, for example, linear temporal logic (LTL) satisfiability solvers. However, for most practical applications, the expressiveness of PSPs is too restricted to enable writing useful requirement specifications, and proving that a set of requirements is inconsistent can be worthless unless a minimal set of conflicting requirements is extracted to help designers to correct a wrong specification. In this paper, we extend PSPs by considering Boolean as well as atomic numerical assertions, we contribute an encoding from extended PSPs to LTL formulas, and we present an algorithm computing inconsistency explanations, i.e., irreducible inconsistent subsets of the original set of requirements. Our extension enables us to reason about the internal consistency of functional requirements which would not be captured by basic PSPs. Experimental results demonstrate that our approach can check and explain (in)consistencies in specifications with nearly two thousand requirements generated using a probabilistic model, and that it enables effective handling of real-world case studies

A new metrics for countries' fitness and products' complexity

Classical economic theories prescribe specialization of countries industrial production. Inspection of the country databases of exported products shows that this is not the case: successful countries are extremely diversified, in analogy with biosystems evolving in a competitive dynamical environment. The challenge is assessing quantitatively the non-monetary competitive advantage of diversification which represents the hidden potential for development and growth. Here we develop a new statistical approach based on coupled non-linear maps, whose fixed point defines a new metrics for the country Fitness and product Complexity. Weshow that a non-linear iteration is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We show that, given the paradigm of economic complexity, the correct and simplest approach to measure the competitiveness of countries is the one presented in this work. Furthermore our metrics appears to be economically well-grounded

Formalizing the Execution Context of Behavior Trees for Runtime Verification of Deliberative Policies

In this paper, we enable automated property verification of deliberative components in robot control architectures. We focus on formalizing the execution context of Behavior Trees (BTs) to provide a scalable, yet formally grounded, methodology to enable runtime verification and prevent unexpected robot behaviors. To this end, we consider a message-passing model that accommodates both synchronous and asynchronous composition of parallel components, in which BTs and other components execute and interact according to the communication patterns commonly adopted in robotic software architectures. We introduce a formal property specification language to encode requirements and build runtime monitors. We performed a set of experiments, both on simulations and on the real robot, demonstrating the feasibility of our approach in a realistic application and its integration in a typical robot software architecture. We also provide an OS-level virtualization environment to reproduce the experiments in the simulated scenario

ΣSFR\Sigma_{\mathrm{SFR}}-M* Diagram: A Valuable Galaxy Evolution Diagnostic to Complement (s)SFR-M* Diagrams

The specific star formation rate (sSFR) is commonly used to describe the level of galaxy star formation (SF) and to select quenched galaxies. However, being a relative measure of the young-to-old population, an ambiguity in its interpretation may arise because a small sSFR can be either because of a substantial previous mass build up, or because SF is low. We show, using large samples spanning 0 < z < 2, that the normalization of SFR by the physical extent over which SF is taking place (i.e., SFR surface density, $\Sigma_{\mathrm{SFR}}$) overcomes this ambiguity. $\Sigma_{\mathrm{SFR}}$ has a strong physical basis, being tied to the molecular gas density and the effectiveness of stellar feedback, so we propose $\Sigma_{\mathrm{SFR}}$-M* as an important galaxy evolution diagram to complement (s)SFR-M* diagrams. Using the $\Sigma_{\mathrm{SFR}}$-M* diagram we confirm the Schiminovich et al. (2007) result that the level of SF along the main sequence today is only weakly mass dependent - high-mass galaxies, despite their redder colors, are as active as blue, low-mass ones. At higher redshift, the slope of the "$\Sigma_{\mathrm{SFR}}$ main sequence" steepens, signaling the epoch of bulge build-up in massive galaxies. We also find that $\Sigma_{\mathrm{SFR}}$ based on the optical isophotal radius more cleanly selects both the starbursting and the spheroid-dominated (early-type) galaxies than sSFR. One implication of our analysis is that the assessment of the inside-out vs. outside-in quenching scenarios should consider both sSFR and $\Sigma_{\mathrm{SFR}}$ radial profiles, because ample SF may be present in bulges with low sSFR (red color).Comment: 16 pages. Accepted to ApJ. Comments on content or relevant missing references welcom

The black hole mass metallicity relation and insights into galaxy quenching

One of the most important questions in astrophysics is what causes galaxies to stop forming stars. Previous studies have shown a tight link between quiescence and black hole mass. Other studies have revealed that quiescence is also associated with 'starvation', the halting of gas inflows, which results in the remaining gas being used up rapidly by star formation and in rapid chemical enrichment. In this work we find the final missing link between these two findings. Using a large sample of galaxies, we uncover the intrinsic dependencies of the stellar metallicity on galaxy properties. In the case of the star-forming galaxies, the stellar metallicity is driven by stellar mass. However, for passive galaxies the stellar metallicity is primarily driven by the black hole mass, as traced by velocity dispersion. This result finally reveals the connection between previous studies, where the integrated effect of black hole feedback prevents gas inflows, starving the galaxy, which is seen by the rapid increase in the stellar metallicity, leading to the galaxy becoming passive.Comment: 20 pages, 6 figures, submitted to Nature Astronom

Diversification versus specialization in complex ecosystems

This is the final version. Available from Public Library of Science via the DOI in this record.The authors confirm that, for approved reasons, some access restrictions apply to the data underlying the findings. The dataset to reproduce all the main findings of the article is available in the zip file enclose in the submission. The authors confirm that they recieved the permission from Bloomberg to share and publish the data attached as a Supporting Information file. The whole worldwide database is available to anyone after a paid subscription to Bloomberg services http://www.bloomberg.com/professional/.By analyzing the distribution of revenues across the production sectors of quoted firms we suggest a novel dimension that drives the firms diversification process at country level. Data show a non trivial macro regional clustering of the diversification process, which underlines the relevance of geopolitical environments in determining the microscopic dynamics of economic entities. These findings demonstrate the possibility of singling out in complex ecosystems those micro-features that emerge at macro-levels, which could be of particular relevance for decision-makers in selecting the appropriate parameters to be acted upon in order to achieve desirable results. The understanding of this micro-macro information exchange is further deepened through the introduction of a simplified dynamic model.EUItalian PNR project “CRISIS-Lab

Extreme value statistics of the halo and stellar mass distributions at high redshift: are JWST results in tension with ΛCDM?

The distribution of dark matter halo masses can be accurately predicted in the lambda cold dark matter (ΛCDM) cosmology. The presence of a single massive halo or galaxy at a particular redshift, assuming some baryon and stellar fraction for the latter, can therefore be used to test the underlying cosmological model. A number of recent measurements of very large galaxy stellar masses at high redshift (z > 8) motivate an investigation into whether any of these objects are in tension with ΛCDM. We use extreme value statistics to generate confidence regions in the mass–redshift plane for the most extreme mass haloes and galaxies. Tests against numerical models show no tension, neither in their dark matter halo masses nor their galaxy stellar masses. However, we find tentative >3σ tension with recent observational determinations of galaxy masses at high redshift from both Hubble Space Telescope and James Webb Space Telescope, despite using conservative estimates for the stellar fraction (f* ∼ 1). Either these galaxies are in tension with ΛCDM, or there are unaccounted for uncertainties in their stellar mass or redshift estimates