pinecone/core-2020-05-10-deduplication huggingface dataset:
Kleene Algebra with Tests and Coq Tools for While Programs

16+3 pagesInternational audienceWe present a Coq library about Kleene algebra with tests, including a proof of their completeness over the appropriate notion of languages, a decision procedure for their equational theory, and tools for exploiting hypotheses of a particular shape in such a theory. Kleene algebra with tests make it possible to represent if-then-else statements and while loops in most imperative programming languages. They were actually introduced by Kozen as an alternative to propositional Hoare logic. We show how to exploit the corresponding Coq tools in the context of program verification by proving equivalences of while programs, correctness of some standard compiler optimisations, Hoare rules for partial correctness, and a particularly challenging equivalence of flowchart schemes
Subformula Linking as an Interaction Method

International audienceCurrent techniques for building formal proofs interactively involve one or several proof languages for instructing an interpreter of the languages to build or check the proof being described. These linguistic approaches have a drawback: the languages are not generally portable, even though the nature of logical reasoning is universal. We propose a somewhat speculative alternative method that lets the user directly manipulate the text of the theorem, using non-linguistic metaphors. It uses a proof formalism based on linking subformulas, which is a variant of deep inference (inference rules are allowed to apply in any formula context) where the relevant formulas in a rule are allowed to be arbitrarily distant. We substantiate the design with a prototype implementation of a linking-based interactive prover for first-order classical linear logic
A note on totally regular variables and Appell sequences in hypercomplex function theory

Series title : Lecture notes in computer science, vol. 7971, ISSN 0302-9743The aim of our contribution is to call attention to the relationship between totally regular variables, introduced by R. Delanghe in 1970, and Appell sequences with respect to the hypercomplex derivative. Under some natural normalization condition the set of all paravector valued totally regular variables defined in the three dimensional Euclidean space will be completely characterized. Together with their integer powers they constitute automatically Appell sequences, since they are isomorphic to the complex variables.Fundação para a Ciência e a Tecnologia (FCT
A note on totally regular variables and Appell sequences in hypercomplex function theory

The aim of our contribution is to call attention to the relationship between totally regular variables, introduced by R. Delanghe in 1970, and Appell sequences with respect to the hypercomplex derivative. Under some natural normalization condition the set of all paravector valued totally regular variables defined in the three dimensional Euclidean space will be completely characterized. Together with their integer powers they constitute automatically Appell sequences, since they are isomorphic to the complex variables
Multilocal programming : a derivative-free filter multistart algorithm

Multilocal programming aims to locate all the local solutions
of an optimization problem. A stochastic method based on a multistart
strategy and a derivative-free filter local search for solving general constrained
optimization problems is presented. The filter methodology is
integrated into a coordinate search paradigm in order to generate a set
of trial approximations that might be acceptable if they improve the
constraint violation or the objective function value relative to the current
one. Preliminary numerical experiments with a benchmark set of
problems show the effectiveness of the proposed method.Fundação para a Ciência e a Tecnologia (FCT
A framework for modular and customizable software analysis

This paper presents a framework for the analysis of software artifacts. We revise and propose techniques that aid in the manipulation and combination of target-language specific tools, and in handling and controlling the results of such tools. We also propose to integrate under our framework techniques that are capable of performing language independent analyses.
The final result of our work is an analysis environment that is modular and flexible and that allows easy and elegant implementations of complex analysis suites.
We finally conduct a proof of concept for our framework by analyzing a well-known, widely used open-source software package.This work is partly funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) within projects FCOMP-01-0124-FEDER-010049, and FCOMP-01-0124-FEDER-022701
Complexity metrics for classSheet models

Lecture Notes in Computer Science Volume 7972, 2013.This paper proposes a set of metrics for the assessment of the complexity of models defining the business logic of spreadsheets. This set can be considered the first step in the direction of building a quality standard for spreadsheet models, that is still to be defined. The computation of concrete metric values has further been integrated under a well-established model-driven spreadsheet development environment, providing a framework for the analysis of spreadsheet models under spreadsheets themselves
The Screen representation of spin networks: 2D recurrence, eigenvalue
  equation for 6j symbols, geometric interpretation and Hamiltonian dynamics

This paper treats 6j symbols or their orthonormal forms as a function of two
variables spanning a square manifold which we call the "screen". We show that
this approach gives important and interesting insight. This two dimensional
perspective provides the most natural extension to exhibit the role of these
discrete functions as matrix elements that appear at the very foundation of the
modern theory of classical discrete orthogonal polynomials. Here we present 2D
and 1D recursion relations that are useful for the direct computation of the
orthonormal 6j, which we name U. We present a convention for the order of the
arguments of the 6j that is based on their classical and Regge symmetries, and
a detailed investigation of new geometrical aspects of the 6j symbols.
Specifically we compare the geometric recursion analysis of Schulten and Gordon
with the methods of this paper. The 1D recursion relation, written as a matrix
diagonalization problem, permits an interpretation as a discrete
Schr\"odinger-like equations and an asymptotic analysis illustrates
semiclassical and classical limits in terms of Hamiltonian evolution.Comment: 14 pages,9 figures, presented at ICCSA 2013 13th International
  Conference on Computational Science and Applicatio
The Screen representation of spin networks. Images of 6j symbols and
  semiclassical features

This article presents and discusses in detail the results of extensive exact
calculations of the most basic ingredients of spin networks, the Racah
coefficients (or Wigner 6j symbols), exhibiting their salient features when
considered as a function of two variables - a natural choice due to their
origin as elements of a square orthogonal matrix - and illustrated by use of a
projection on a square "screen" introduced recently. On these screens, shown
are images which provide a systematic classification of features previously
introduced to represent the caustic and ridge curves (which delimit the
boundaries between oscillatory and evanescent behaviour according to the
asymptotic analysis of semiclassical approaches). Particular relevance is given
to the surprising role of the intriguing symmetries discovered long ago by
Regge and recently revisited; from their use, together with other newly
discovered properties and in conjunction with the traditional combinatorial
ones, a picture emerges of the amplitudes and phases of these discrete
wavefunctions, of interest in wide areas as building blocks of basic and
applied quantum mechanics.Comment: 16 pages, 13 figures, presented at ICCSA 2013 13th International
  Conference on Computational Science and Applicatio
Impact assessment of interregional government transfers in Brazil: an input-output approach

Redistributive policies carried out by the central government through interregional government transfers is a relevant feature of the Brazilian federal fiscal system. Regional shares of the central government revenues in the poorer regions have been recurrently smaller than the shares of central government expenditures in those regions. Appeal to core-periphery outcomes could be made, as São Paulo, the wealthiest state in the country, concentrated, in 2005, over 40% of total Federal tax revenue, receiving less than 35% of Federal expenditures. These figures suggest a redistribution of public funds from the spatial economic core of the economy to the peripheral areas. This paper investigates the role interregional transfers play in the redistribution of activities in the country, using an interregional input-output approach. Counterfactual simulations allow us to estimate some costs and benefits, for the core and periphery respectively, from such fiscal mechanisms.
Decremental Learning of Evolving Fuzzy Inference Systems, Application to Handwritten Gestures Recognition

International audienceThis paper tackles the problem of incremental and decremental learning of an evolving and customizable fuzzy inference system for classification. We explain the interest of integrating a forgetting capacity in such an evolving system to improve its performances in changing environment. In this paper, we describe two decremental learning strategies, to introduce a forgetting capacity in evolving fuzzy inference systems. Both techniques use a sliding window to introduce forgetting in the optimization process of fuzzy rules conclusions. The first approach is based on a downdating technique of least squares solutions for unlearning old data. The second integrates differed directional forgetting in the covariance matrices used in the recursive least square algorithm. These techniques are first evaluated on handwritten gesture recognition tasks in changing environments. They are also evaluated on some well-known classification benchmarks. In particular, it is shown that decremental learning allow to adapt to concept drifts. It is also demonstrated that decremental learning is necessary to maintain the system capacity of learning new classes over time, making decremental learning essential for the life-time use of an evolving and customizable classification system
Predicting regression test failures using genetic algorithm-selected dynamic performance analysis metrics

A novel framework for predicting regression test failures is proposed. The basic principle embodied in the framework is to use performance analysis tools to capture the runtime behaviour of a program as it executes each test in a regression suite. The performance information is then used to build a dynamically predictive model of test outcomes. Our framework is evaluated using a genetic algorithm for dynamic metric selection in combination with state-of-the-art machine learning classifiers. We show that if a program is modified and some tests subsequently fail, then it is possible to predict with considerable accuracy which of the remaining tests will also fail which can be used to help prioritise tests in time constrained testing environments
Ontology-based data access with databases: a short course

Ontology-based data access (OBDA) is regarded as a key ingredient of the new generation of information systems. In the OBDA paradigm, an ontology defines a high-level global schema of (already existing) data sources and provides a vocabulary for user queries. An OBDA system rewrites such queries and ontologies into the vocabulary of the data sources and then delegates the actual query evaluation to a suitable query answering system such as a relational database management system or a datalog engine. In this chapter, we mainly focus on OBDA with the ontology language OWL 2QL, one of the three profiles of the W3C standard Web Ontology Language OWL 2, and relational databases, although other possible languages will also be discussed. We consider different types of conjunctive query rewriting and their succinctness, different architectures of OBDA systems, and give an overview of the OBDA system Ontop
Handling Incoming Beliefs

Most logic-based approaches to knowledge and belief change in artificial intelligence assume that when a new piece of information comes up, it should be merely added to the current beliefs or knowledge when this does not lead to inconsistency. This paper addresses situations where this assumption does not hold. The focus is on the construction of Boolean standard-logic knowledge and belief bases in this context. We propose an approach to handle incoming beliefs that can require some formulas reconstruction or a form of preemption to be performed
A Fully Verified Executable LTL Model Checker

We present an LTL model checker whose code has been completely verified using the Isabelle theorem prover. The checker consists of over 4000 lines of ML code. The code is produced using recent Isabelle technology called the Refinement Framework, which allows us to split its correctness proof into (1) the proof of an abstract version of the checker, consisting of a few hundred lines of “formalized pseudocode”, and (2) a verified refinement step in which mathematical sets and other abstract structures are replaced by implementations of efficient structures like red-black trees and functional arrays. This leads to a checker that, while still slower than unverified checkers, can already be used as a trusted reference implementation against which advanced implementations can be tested. We report on the structure of the checker, the development process, and some experiments on standard benchmarks
Importance Splitting for Statistical Model Checking Rare Properties

International audienceStatistical model checking avoids the intractable growth of states associated with probabilistic model checking by estimating the probability of a property from simulations. Rare properties are often important, but pose a challenge for simulation-based approaches: the relative error of the estimate is unbounded. A key objective for statistical model checking rare events is thus to reduce the variance of the estimator. Importance splitting achieves this by estimating a sequence of conditional probabilities, whose product is the required result. To apply this idea to model checking it is necessary to define a score function based on logical properties, and a set of levels that delimit the conditional probabilities. In this paper we motivate the use of importance splitting for statistical model checking and describe the necessary and desirable properties of score functions and levels. We illustrate how a score function may be derived from a property and give two importance splitting algorithms: one that uses fixed levels and one that discovers optimal levels adaptively
Under-approximating Cut Sets for Reachability in Large Scale Automata Networks

International audienceIn the scope of discrete finite-state models of interacting components, we present a novel algorithm for identifying sets of local states of components whose activity is necessary for the reachability of a given local state. If all the local states from such a set are disabled in the model, the concerned reachability is impossible. Those sets are referred to as cut sets and are computed from a particular abstract causality structure, so-called Graph of Local Causality, inspired from previous work and generalised here to finite automata networks. The extracted sets of local states form an under-approximation of the complete minimal cut sets of the dynamics: there may exist smaller or additional cut sets for the given reachability. Applied to qualitative models of biological systems, such cut sets provide potential therapeutic targets that are proven to prevent molecules of interest to become active, up to the correctness of the model. Our new method makes tractable the formal analysis of very large scale networks, as illustrated by the computation of cut sets within a Boolean model of biological pathways interactions gathering more than 9000 components
QUAIL: A Quantitative Security Analyzer for Imperative Code

International audienceQuantitative security analysis evaluates and compares how effectively a system protects its secret data. We introduce QUAIL, the first tool able to perform an arbitrary-precision quantitative analysis of the security of a system depending on private information. QUAIL builds a Markov Chain model of the system's behavior as observed by an attacker, and computes the correlation between the system's observable output and the behavior depending on the private information, obtaining the expected amount of bits of the secret that the attacker will infer by observing the system. QUAIL is able to evaluate the safety of randomized protocols depending on secret data, allowing to verify a security protocol's effectiveness. We experiment with a few examples and show that QUAIL's security analysis is more accurate and revealing than results of other tools
Validating Library Usage Interactively

Programmers who develop large, mature applications often 
want to optimize the performance of their program without changing 
the semantics of the program. They often do so by changing how their 
program invokes a library function or a function provided by another 
module of the program. Unfortunately, once a programmer makes such 
an optimization, it is difficult for him to determine that the optimization 
does not change the semantics of the original program, because the orig- 
inal and optimized programs are equivalent only due to subtle, implicit 
assumptions about library functions called by the programs. 

In this work, we present an interactive program analysis that a program- 
mer can apply to determine that his optimization does not change the 
behavior of a program. Our analysis casts the problem of validating an 
optimization as an abductive inference problem in the context of checking 
program equivalence. Our analysis solves the abductive equivalence prob- 
lem by interacting with the programmer so that the programmer imple- 
ments a solver for a logical theory that models library functions invoked 
by the program. We have used our analysis to validate 
optimizations from a set real-world, mature applications consisting 
of the Apache webserver, the Mozilla software suite, and the MySQL 
database
Learning epistemic actions in model-free memory-free reinforcement learning: experiments with a neuro-robotic model

Passive sensory processing is often insufficient to guide biological organisms in complex environments. Rather, behaviourally relevant information can be accessed by performing so-called epistemic actions that explicitly aim at unveiling hidden information. However, it is still unclear how an autonomous agent can learn epistemic actions and how it can use them adaptively. In this work, we propose a definition of epistemic actions for POMDPs that derive from their characterizations in cognitive science and classical planning literature. We give theoretical insights about how partial observability and epistemic actions can affct the learning process and performance in the extreme conditions of model-free and memory-free reinforcement learning where hidden information cannot be represented. We finally investigate these concepts using an integrated eye-arm neural architecture for robot control, which can use its effctors to execute epistemic actions and can exploit the actively gathered information to effiently accomplish a seek-and-reach task
Biomimetic Spatial and Temporal (4D) Design and Fabrication

We imagine the built environment of the future as a ‘bio-hybrid machine for living in’ that will sense and react to activities within the space in order to provide experiences and services that will elevate quality of life while coexisting seamlessly with humans and the natural environment. The study of Hierarchical design in biological materials has the potential to alter the way designers/ engineers/ craftsmen of the future engage with materials in order to realise such visions. Current techniques for making/ experimenting/ developing ideas are limited. Innovations in digital manufacturing technologies such as jacquard weaving and 3D printing promise the realisation of beneficial architectures from micro to macro scale previously impossible to achieve using conventional methodologies. This poster presents a novel landscape of opportunities for the exploration and exploitation of biological mechanisms into human centred manufactured systems
Punishment and Gossip: Sustaining Cooperation in a Public Goods Game

In an environment in which free-riders are better off than cooperators, social control is required to foster and maintain coopera- tion. There are two main paths through which social control can be ap- plied: punishment and reputation. Our experiments explore the efficacy of punishment and reputation on cooperation rates, both in isolation and in combination. Using a Public Goods Game, we are interested in assessing how cooperation rates change when agents can play one of two different reactive strategies, i.e., they can pay a cost in order to reduce the payoff of free-riders, or they can know others\u27 reputation and then either play defect with free-riders, or refuse to interact with them. Co- operation is maintained at a high level through punishment, but also reputation-based partner selection proves effective in maintaining coop- eration. However, when agents are informed about free-riders\u27 reputation and play Defect, cooperation decreases. Finally, a combination of punish- ment and reputation-based partner selection leads to higher cooperation rates
Moral Guilt : An Agent-Based Model Analysis

In this article we analyze the influence of a concrete moral emotion (i.e. moral guilt) on strategic decision making. We present a normal form Prisoner’s Dilemma with a moral component. We assume that agents evaluate the game’s outcomes with respect to their ideality degree (i.e. how much a given outcome conforms to the player’s moral values), based on two proposed notions on ethical preferences: Harsanyi’s and Rawls’. Based on such game, we construct and agent-based model of moral guilt, where the intensity of an agent’s guilt feeling plays a determinant role in her course of action. Results for both constructions of ideality are analyzed
Reasoning about Choice

We present a logic for reasoning about choice. Choice ctl (c-ctl) extends the well-known branching-time temporal logic ctl with choice modalities, " &#9674; " and "&#9633;". An example c-ctl formula is &#9674; AF happy, asserting that there exists a choice that will lead to happiness. c-ctl is related to both stit logics and temporal cooperation logics such as atl, but has a much simpler and (we argue) more intuitive syntax and semantics. After presenting the logic, we investigate the properties of the language. We characterise the complexity of the c-ctl model checking problem, investigate some validities, and propose multi-agent extensions to the logic