We present a new model for concurrent programming, which we call AbstrAct. A system is specified through collections of rules defining all possible state transformations that may occur. The activity of a system is dri...
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Virtual assembly allows human operators to use their hands manipulating the graphics representation of machinery parts and programming assembly tasks directly in a three-dimensional operation space. The imprecise meas...
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This paper describes a new approach on optimization of constraint satisfaction problems (CSPs) by means of substituting sub-CSPs with locally consistent regular membership constraints. The purpose of this approach is ...
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Evolutionary algorithms and, in particular, Genetic programming (GP) are increasingly being applied to the problem of evolving term-weighting schemes in Information Retrieval (IR). One fundamental problem with the sol...
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Evolutionary algorithms and, in particular, Genetic programming (GP) are increasingly being applied to the problem of evolving term-weighting schemes in Information Retrieval (IR). One fundamental problem with the solutions generated by these stochastic processes is that they are often difficult to analyse. A number of questions regarding these evolved term-weighting schemes remain unanswered. One interesting question is;do different runs of the GP process bring us to similar points in the solution space? This paper deals with determining a number of measures of the distance between the ranked lists (phenotype) returned by different term-weighting schemes. Using these distance measures, we develop trees that show the phenotypic distance between these termweighting schemes. This framework gives us a representation of where these evolved solutions lie in the solution space. Finally, we evolve several global term-weighting schemes and show that this framework is indeed useful for determining the relative closeness of these schemes and for determining the expected performance on general test data.
Capturing the uncertain aspects in cyber threat analyses is an important part of a wide range of efforts, including diagnostics, threat evaluation, and preventing attacks. However, there has been insufficient research...
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作者:
PARIGOT, MEquipe de Logique
CNRS UA 753 Université Paris 7 UFR de Mathématiques 2 place Jussieu PARIS Cedex 05 75251 France
We analyse the algorithmic properties of programs induced by the choice of the representation of data in lambda-calculus. From a logical point of view there are two canonical ways of defining the data types: the itera...
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The proceedings contain 21 papers. The special focus in this conference is on Evaluation Strategies and programming Tools. The topics include: Lazy remote procedure call and its implementation;efficient evaluation str...
ISBN:
(纸本)3540611436
The proceedings contain 21 papers. The special focus in this conference is on Evaluation Strategies and programming Tools. The topics include: Lazy remote procedure call and its implementation;efficient evaluation strategies for structured concurrency constructs in parallel scheme systems;the semantics of pcall and fork in the presence of first-class continuations and side-effects;understanding the performance of parallel symbolic programs;a debugging scheme for fine-grain threads on massively parallel processors with a small amount of log information;distributed prograph;experiences with strong moding in concurrent logic/constraint programming;portable parallel irregular applications;understanding language support for irregular parallelism;efficient parallel graph coloring with prioritization;group-based fields;parallel symbolic computing in cid;an overview of MPC++ - extended abstract;fault tolerance via replication in coarse grain data-flow;experience with parallel symbolic applications in orca;a portable parallel implementation of a concurrent logicprogramming language;DMEROON, overview of a distributed class-based causally-coherent data model;lessons from the experience;the role of distributed lisp in open hypermedia information systems;foundations for a virtual multicomputer - progress report and process calculi at work - an account of the LCS project.
Simultaneous spatial constraint problems can be approached algebraically, geometrically, or constructively. We examine how each approach performs, using several example problems, especially constraint problems involvi...
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The Directed Acyclic Graph (DAG), which can be generated by object oriented modelling languages, is often the most natural way of representing and manipulating a dynamic optimization problem. With this representation,...
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The Directed Acyclic Graph (DAG), which can be generated by object oriented modelling languages, is often the most natural way of representing and manipulating a dynamic optimization problem. With this representation, it is possible to step-by-step reformulate an (infinite dimensional) dynamic optimization problem into a (finite dimensional) non-linear program (NLP) by parametrizing the state and control trajectories. We introduce CasADi, a minimalistic computer algebra system written in completely self-contained C++. The aim of the tool is to offer the benifits of a computer algebra to developers of C++ code, without the overhead usually associated with such systems. In particular, we use the tool to implement automatic differentiation, AD. For maximum efficiency, CasADi works with two different graph representations interchangeably: One supporting only scalar-valued, built-in unary and binary operations and no branching, similar to the representation used by today's tools for automatic differentiation by operator overloading. Secondly, a representation supporting matrixvalued operations, branchings such as if-statements as well as function calls to arbitrary functions (e.g. ODE/DAE integrators). We show that the tool performs favorably compared to CppAD and ADOL-C, two state-of-the-art tools for AD by operator overloading. We also show how the tool can be used to solve a simple optimal control problem, minimal fuel rocket flight, by implementing a simple ODE integrator with sensitivity capabilities and solving the problem with the NLP solver IPOPT. In the last example, we show how we can use the tool to couple the modelling tool JModelica with the optimal control software ACADO Toolkit.
Neural networks have proven very useful in the field of pattern classification by mapping input patterns into one of several categories. The most popular methods of training neural networks use gradient descent techni...
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ISBN:
(纸本)1565550072
Neural networks have proven very useful in the field of pattern classification by mapping input patterns into one of several categories. The most popular methods of training neural networks use gradient descent techniques to minimize mean square error measured against a training set. The composition of this training set, therefore, will determine the performance of the resulting trained network. Deficiencies in the training set, such as unequal class representation or ineffective training vectors will diminish the network's ultimate performance. Additionally, the characteristics of the training set will implicitly set network performance goals that may or may not match the desired goals of the network designer. This paper investigates the utilization of a fuzzy system to overcome these training set inadequacies by incorporating performance goals into the training strategy. Fuzzy control is used to modify the learning rate parameter during backpropagation training. The method is tested using artificial training data and real-world hyperspectral imagery.
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