TRAVOS: Trust and Reputation in the Context of Inaccurate Information Sources

In many dynamic open systems, agents have to interact with one another to achieve their goals. Here, agents may be self-interested, and when trusted to perform an action for another, may betray that trust by not performing the action as required. In addition, due to the size of such systems, agents will often interact with other agents with which they have little or no past experience. There is therefore a need to develop a model of trust and reputation that will ensure good interactions among software agents in large scale open systems. Against this background, we have developed TRAVOS (Trust and Reputation model for Agent-based Virtual OrganisationS) which models an agent's trust in an interaction partner. Specifically, trust is calculated using probability theory taking account of past interactions between agents, and when there is a lack of personal experience between agents, the model draws upon reputation information gathered from third parties. In this latter case, we pay particular attention to handling the possibility that reputation information may be inaccurate

Sequential Decision Making with Untrustworthy Service Providers

In this paper, we deal with the sequential decision making problem of agents operating in computational economies, where there is uncertainty regarding the trustworthiness of service providers populating the environment. Specifically, we propose a generic Bayesian trust model, and formulate the optimal Bayesian solution to the exploration-exploitation problem facing the agents when repeatedly interacting with others in such environments. We then present a computationally tractable Bayesian reinforcement learning algorithm to approximate that solution by taking into account the expected value of perfect information of an agent's actions. Our algorithm is shown to dramatically outperform all previous finalists of the international Agent Reputation and Trust (ART) competition, including the winner from both years the competition has been run

The ART of IAM: The Winning Strategy for the 2006 Competition

In many dynamic open systems, agents have to interact with one another to achieve their goals. Here, agents may be self-interested, and when trusted to perform an action for others, may betray that trust by not performing the actions as required. In addition, due to the size of such systems, agents will often interact with other agents with which they have little or no past experience. This situation has led to the development of a number of trust and reputation models, which aim to facilitate an agent's decision making in the face of uncertainty regarding the behaviour of its peers. However, these multifarious models employ a variety of different representations of trust between agents, and measure performance in many different ways. This has made it hard to adequately evaluate the relative properties of different models, raising the need for a common platform on which to compare competing mechanisms. To this end, the ART Testbed Competition has been proposed, in which agents using different trust models compete against each other to provide services in an open marketplace. In this paper, we present the winning strategy for this competition in 2006, provide an analysis of the factors that led to this success, and discuss lessons learnt from the competition about issues of trust in multiagent systems in general. Our strategy, IAM, is Intelligent (using statistical models for opponent modelling), Abstemious (spending its money parsimoniously based on its trust model) and Moral (providing fair and honest feedback to those that request it)

A truthful online mechanism for resource allocation in fog computing

Fog computing is a promising Internet of Things (IoT) paradigm in which data is processed near its source. Here, efficient resource allocation mechanisms are needed to assign limited fog resources to competing IoT tasks. To this end, we consider two challenges: (1) near-optimal resource allocation in a fog computing system; (2) incentivising self-interested fog users to report their tasks truthfully. To address these challenges, we develop a truthful online resource allocation mechanism called flexible online greedy. The key idea is that the mechanism only commits a certain amount of computational resources to a task when it arrives. However, when and where to allocate resources stays flexible until the completion of the task. We compare our mechanism to four benchmarks and show that it outperforms all of them in terms of social welfare by up to 10% and achieves a social welfare of about 90% of the offline optimal upper bound

Redox-dependent gating of VDAC by mitoNEET.

MitoNEET is an outer mitochondrial membrane protein essential for sensing and regulation of iron and reactive oxygen species (ROS) homeostasis. It is a key player in multiple human maladies including diabetes, cancer, neurodegeneration, and Parkinson's diseases. In healthy cells, mitoNEET receives its clusters from the mitochondrion and transfers them to acceptor proteins in a process that could be altered by drugs or during illness. Here, we report that mitoNEET regulates the outer-mitochondrial membrane (OMM) protein voltage-dependent anion channel 1 (VDAC1). VDAC1 is a crucial player in the cross talk between the mitochondria and the cytosol. VDAC proteins function to regulate metabolites, ions, ROS, and fatty acid transport, as well as function as a "governator" sentry for the transport of metabolites and ions between the cytosol and the mitochondria. We find that the redox-sensitive [2Fe-2S] cluster protein mitoNEET gates VDAC1 when mitoNEET is oxidized. Addition of the VDAC inhibitor 4,4'-diisothiocyanatostilbene-2,2'-disulfonate (DIDS) prevents both mitoNEET binding in vitro and mitoNEET-dependent mitochondrial iron accumulation in situ. We find that the DIDS inhibitor does not alter the redox state of MitoNEET. Taken together, our data indicate that mitoNEET regulates VDAC in a redox-dependent manner in cells, closing the pore and likely disrupting VDAC's flow of metabolites

On the response of a particle detector in Anti-de Sitter spacetime

We consider the vacuum response of a particle detector in Anti-de Sitter spacetime, and in particular analyze how spacetime features such as curvature and dimensionality affect the response spectrum of an accelerated detector. We calculate useful limits on Wightman functions, analyze the dynamics of the detector in terms of vacuum fluctuations and radiation reactions, and discuss the thermalization process for the detector. We also present a generalization of the GEMS approach and obtain the Gibbons-Hawking temperature of de Sitter spacetime as an embedded Unruh temperature in a curved Anti-de Sitter spacetime.Comment: 13 pages, no figures, accepted for publication in Class. Quantum Gra

Variação demográfica causada por exploração florestal no banco de mudas de espécies florestais em resposta a diferentes tamanhos de aberturas no dossel da floresta.

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Banco de sementes de floresta tropical úmida no município de Moju, PA.

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GammaCore: The Compton Observatory research environment

The Compton Observatory Science Support Center (COSSC) is developing a coherent analysis environment for the analysis of Compton and other gamma-ray astronomy data. This environment, GammaCore, allows the astronomer to access the data analysis systems developed at the Principal Investigator (PI) sites for the four Compton Observatory instruments. In addition users have access to standard astronomical tools such as IRAF, IDL, and XANADU. The user interface of GammaCore is the AGCL (AnswerGarden Command Language), developed at the AXAF Science Center. The parameter interface supported by the AGCL allows GammaCore to access all PI software systems in a uniform fashion. These systems are quite different, having been developed independently on heterogeneous systems without much concern for general portability. The data kibitzer concept, where a window running in a specific PI environment is controlled by the AGCL, has been used extensively. Users can choose to view what is going on in the native environment, to use the window to control PI software directly, or to ignore the PI systems entirely and to work only through the homogeneous AGCL interface. Software developed at the COSSC is also integrated within GammaCore. Extensive facilities for conversions of PI data formats to and from FITS have been developed. Access to the Compton data archive and catalogs will also be completely integrated with the GammaCore. Users can retrieve any publicly available Compton data. This paper examines the issues that have arisen in attempting to meld these widely diverse systems. The advantages and limitations of the parameter interface and the kibitzer are discussed along with issues of data portability, documentation, and the feasibility of multi-instrument analysis. Limited capabilities are now available within GammaCore with significant enhancements planned over the coming year. An implementation including all PI systems will be available within that time. Instructions on how to access GammaCore and how to get more information are given