19,926 research outputs found
Verification of Information Flow Properties under Rational Observation
Information flow properties express the capability for an agent to infer
information about secret behaviours of a partially observable system. In a
language-theoretic setting, where the system behaviour is described by a
language, we define the class of rational information flow properties (RIFP),
where observers are modeled by finite transducers, acting on languages in a
given family . This leads to a general decidability criterion for
the verification problem of RIFPs on , implying
PSPACE-completeness for this problem on regular languages. We show that most
trace-based information flow properties studied up to now are RIFPs, including
those related to selective declassification and conditional anonymity. As a
consequence, we retrieve several existing decidability results that were
obtained by ad-hoc proofs.Comment: 19 pages, 7 figures, version extended from AVOCS'201
Learning Hybrid Process Models From Events: Process Discovery Without Faking Confidence
Process discovery techniques return process models that are either formal
(precisely describing the possible behaviors) or informal (merely a "picture"
not allowing for any form of formal reasoning). Formal models are able to
classify traces (i.e., sequences of events) as fitting or non-fitting. Most
process mining approaches described in the literature produce such models. This
is in stark contrast with the over 25 available commercial process mining tools
that only discover informal process models that remain deliberately vague on
the precise set of possible traces. There are two main reasons why vendors
resort to such models: scalability and simplicity. In this paper, we propose to
combine the best of both worlds: discovering hybrid process models that have
formal and informal elements. As a proof of concept we present a discovery
technique based on hybrid Petri nets. These models allow for formal reasoning,
but also reveal information that cannot be captured in mainstream formal
models. A novel discovery algorithm returning hybrid Petri nets has been
implemented in ProM and has been applied to several real-life event logs. The
results clearly demonstrate the advantages of remaining "vague" when there is
not enough "evidence" in the data or standard modeling constructs do not "fit".
Moreover, the approach is scalable enough to be incorporated in
industrial-strength process mining tools.Comment: 25 pages, 12 figure
The case of online trust
âThe original publication is available at www.springerlink.comâ. Copyright SpringerThis paper contributes to the debate on online trust addressing the problem of whether an online environment satisfies the necessary conditions for the emergence of trust. The paper defends the thesis that online environments can foster trust, and it does so in three steps. Firstly, the arguments proposed by the detractors of online trust are presented and analysed. Secondly, it is argued that trust can emerge in uncertain and risky environments and that it is possible to trust online identities when they are diachronic and sufficient data are available to assess their reputation. Finally, a definition of trust as a second-order property of first-order relation is endorsed in order to present a new definition of online trust. According to such a definition, online trust is an occurrence of trust that specifically qualifies the relation of communication ongoing among individuals in digital environments. On the basis of this analysis, the paper concludes by arguing that online trust promotes the emergence of social behaviours rewarding honest and transparent communications.Peer reviewe
Talking Nets: A Multi-Agent Connectionist Approach to Communication and Trust between Individuals
A multi-agent connectionist model is proposed that consists of a collection of individual recurrent networks that communicate with each other, and as such is a network of networks. The individual recurrent networks simulate the process of information uptake, integration and memorization within individual agents, while the communication of beliefs and opinions between agents is propagated along connections between the individual networks. A crucial aspect in belief updating based on information from other agents is the trust in the information provided. In the model, trust is determined by the consistency with the receiving agentsâ existing beliefs, and results in changes of the connections between individual networks, called trust weights. Thus activation spreading and weight change between individual networks is analogous to standard connectionist processes, although trust weights take a specific function. Specifically, they lead to a selective propagation and thus filtering out of less reliable information, and they implement Griceâs (1975) maxims of quality and quantity in communication. The unique contribution of communicative mechanisms beyond intra-personal processing of individual networks was explored in simulations of key phenomena involving persuasive communication and polarization, lexical acquisition, spreading of stereotypes and rumors, and a lack of sharing unique information in group decisions
Geometrical-topological correlation in structures
The topology of polyhedra, tessellations and networks is described as to their mapping in Schlaefli space. A description of the topological form index is given and it is applied to these structural classes in terms of their geometries
Enterprise model verification and validation : an approach
This article presents a verification and validation approach which is used here in order to complete the classical tool box the industrial user may utilize in enterprise modeling and integration domain. This approach, which has been defined independently from any application domain is based on several formal concepts and tools presented in this paper. These concepts are property concepts, property reference matrix, properties graphs, enterprise modeling domain ontology, conceptual graphs and formal reasoning mechanisms
Distributed Computation as Hierarchy
This paper presents a new distributed computational model of distributed
systems called the phase web that extends V. Pratt's orthocurrence relation
from 1986. The model uses mutual-exclusion to express sequence, and a new kind
of hierarchy to replace event sequences, posets, and pomsets. The model
explicitly connects computation to a discrete Clifford algebra that is in turn
extended into homology and co-homology, wherein the recursive nature of objects
and boundaries becomes apparent and itself subject to hierarchical recursion.
Topsy, a programming environment embodying the phase web, is available from
www.cs.auc.dk/topsy.Comment: 16 pages, 3 figure
Regularizing Deep Networks by Modeling and Predicting Label Structure
We construct custom regularization functions for use in supervised training
of deep neural networks. Our technique is applicable when the ground-truth
labels themselves exhibit internal structure; we derive a regularizer by
learning an autoencoder over the set of annotations. Training thereby becomes a
two-phase procedure. The first phase models labels with an autoencoder. The
second phase trains the actual network of interest by attaching an auxiliary
branch that must predict output via a hidden layer of the autoencoder. After
training, we discard this auxiliary branch.
We experiment in the context of semantic segmentation, demonstrating this
regularization strategy leads to consistent accuracy boosts over baselines,
both when training from scratch, or in combination with ImageNet pretraining.
Gains are also consistent over different choices of convolutional network
architecture. As our regularizer is discarded after training, our method has
zero cost at test time; the performance improvements are essentially free. We
are simply able to learn better network weights by building an abstract model
of the label space, and then training the network to understand this
abstraction alongside the original task.Comment: to appear at CVPR 201
Model-driven design, simulation and implementation of service compositions in COSMO
The success of software development projects to a large extent depends on the quality of the models that are produced in the development process, which in turn depends on the conceptual and practical support that is available for modelling, design and analysis. This paper focuses on model-driven support for service-oriented software development. In particular, it addresses how services and compositions of services can be designed, simulated and implemented. The support presented is part of a larger framework, called COSMO (COnceptual Service MOdelling). Whereas in previous work we reported on the conceptual support provided by COSMO, in this paper we proceed with a discussion of the practical support that has been developed. We show how reference models (model types) and guidelines (design steps) can be iteratively applied to design service compositions at a platform independent level and discuss what tool support is available for the design and analysis during this phase. Next, we present some techniques to transform a platform independent service composition model to an implementation in terms of BPEL and WSDL. We use the mediation scenario of the SWS challenge (concerning the establishment of a purchase order between two companies) to illustrate our application of the COSMO framework
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