1,721,009 research outputs found
Control of large distributed systems using games with pure strategy nash equilibria
No full textControl mechanisms for optimisation in large distributed systems cannot be constructed based on traditional methods of control because they are typically characterised by distributed information and costly and/or noisy communication. Furthermore, noisy observations and dynamism are also inherent to these systems, so their control mechanisms need to be flexible, agile and robust in the face of these characteristics. In such settings, a good control mechanism should satisfy the following four design requirements: (i) it should produce high quality solutions, (ii) it should be robustness and flexibility in the face of additions, removals and failures of components, (iii) it should operate by making limited use of communication, and (iv) its operation should be computational feasible. Against this background, in order to satisfy these requirements, in this thesis we adopt a design approach based on dividing control over the system across a team of self–interested agents. Such multi–agent systems (MAS) are naturally distributed (matching the application domains in question), and by pursing their own private goals, the agents can collectively implement robust, flexible and scalable control mechanisms. In more detail, the design approach we adopt is (i) to use games with pure strategy Nash equilibria as a framework or template for constructing the agents’ utility functions, such that good solutions to the optimisation problem arise at the pure strategy Nash equilibria of the game, and (ii) to derive distributed techniques for solving the games for their Nash equilibria. The specific problems we tackle can be grouped into four main topics. First, we investigate a class of local algorithms for distributed constraint optimisation problems (DCOPs). We introduce a unifying analytical framework for studying such algorithms, and develop a parameterisation of the algorithm design space, which represents a mapping from the algorithms’ components to their performance according to each of our design requirements. Second, we develop a game–theoretic control mechanism for distributed dynamic task allocation and scheduling problems. The model in question is an expansion of DCOPs to encompass dynamic problems, and the control mechanism we derive builds on the insights from our first topic to address our four design requirements. Third, we elaborate a general class of problems including DCOPs with noisy rewards and state observations, which are realistic traits of great concern in real–world problems, and derive control mechanisms for these environments. These control mechanism allow the agents to either learn their reward functions or decide when to make observations of the world’s state and/or communicate their beliefs over the state of the world, in such a manner that they perform well according to our design requirements. Fourth, we derive an optimal algorithm for computing and optimising over pure strategy Nash equilibria in games with sparse interaction structure. By exploiting the structure present in many multi-agent interactions, this distributed algorithm can efficiently compute equilibria that optimise various criteria, thus reducing the computational burden on any one agent and operating using less communication than an equivalent centralised algorithms.For each of these topics, the control mechanisms that we derive are developed such that they perform well according to all four f our design requirements. In sum, by making the above contributions to these specific topics, we demonstrate that the general approach of using games with pure strategy Nash equilibria as a template for designing MAS produces good control mechanisms for large distributed systems
Learning in unknown reward games: application to sensor networks
No full textThis paper demonstrates a decentralised method for optimisation using game-theoretic multi-agent techniques, applied to a sensor network management problem. Our first major contribution is to show how the marginal contribution utility design is used to construct a unknown-reward potential game formulation of the problem. This formulation exploits the sparse structure of sensor networkproblems, and allows us to apply a bound to the price of anarchy of the Nash equilibria of theinduced game. Furthermore, since the game is a potential game, solutions can be found using multiagentlearning techniques. The techniques we derive use Q-learning to estimate an agent’s rewards,while an action adaptation process responds to an agent’s opponents’ behaviour. However, there aremany different algorithmic configurations that could be used to solve these games. Thus, our secondmajor contribution is an extensive evaluation of several action adaptation processes. Specifically,we compare six algorithms across a variety of parameter settings to ascertain the quality of thesolutions they produce, their speed of convergence, and their robustness to pre-specified parameterchoices. Our results show that they each perform similarly across a wide range of parameters.There is, however, a significant effect from moving to a learning policy with sampling probabilitiesthat go to zero too quickly for rewards to be accurately estimated
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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