79 resultados para Game strategies


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Efficacy of commercial wireless networks can be substantially enhanced through large-scale cooperation among involved entities such as providers and customers. The success of such cooperation is contingent upon the design of judicious resource allocation strategies that ensure that the individuals' payoffs are commensurate to the resources they offer to the coalition. The resource allocation strategies depend on which entities are decision-makers and whether and how they share their aggregate payoffs. Initially, we consider the scenario where the providers are the only decision-makers and they do not share their payoffs. We formulate the resource allocation problem as a nontransferable payoff coalitional game and show that there exists a cooperation strategy that leaves no incentive for any subset of providers to split from the grand coalition, i.e., the core of the game is nonempty. To compute this cooperation strategy and the corresponding payoffs, we subsequently relate this game and its core to an exchange market setting and its equilibrium, which can be computed by several efficient algorithms. Next, we investigate cooperation when customers are also decision-makers and decide which provider to subscribe to based on whether there is cooperation. We formulate a coalitional game in this setting and show that it has a nonempty core. Finally, we extend the formulations and results to the cases where the payoffs are vectors and can be shared selectively.

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Development of new multifunctional nanostructures relies on the ability to make new materials at the nanoscale with control over size, shape and composition. While this control is extremely important to tune several properties, an alternative strategy is to create active interfaces between two or more nanostructures to form nanoscale heterostructures. In these heterostructures, the interfaces play a key role in stabilizing and enhancing the efficiency of the individual components for various applications. In this article, we discuss synthesis methods of different types of nanoscale heterostructures and the role of interfaces in various applications. We present the current state-of-the-art in designing heterostructures and possible upcoming synthetic strategies with their advantages and disadvantages. We present how such heterostructures are highly efficient for catalytic, photovoltaic and nanoelectronic applications drawing several examples from our own studies and from the literature.

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When an Indian prime minister publicly admits that India has fallen behind China, it is news. Manmohan Singh's statement last January at the Indian Science Congress in Bhubaneswar that this is so with respect to scientific research, and that “India's relative position in the world of science has been declining”, has rung alarm bells. Singh was not springing anything new on Indian scientists; many of us will admit that things are not well1. Recognizing the problem is the first step towards reversing this slide.

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Comparison of multiple protein structures has a broad range of applications in the analysis of protein structure, function and evolution. Multiple structure alignment tools (MSTAs) are necessary to obtain a simultaneous comparison of a family of related folds. In this study, we have developed a method for multiple structure comparison largely based on sequence alignment techniques. A widely used Structural Alphabet named Protein Blocks (PBs) was used to transform the information on 3D protein backbone conformation as a ID sequence string. A progressive alignment strategy similar to CLUSTALW was adopted for multiple PB sequence alignment (mulPBA). Highly similar stretches identified by the pairwise alignments are given higher weights during the alignment. The residue equivalences from PB based alignments are used to obtain a three dimensional fit of the structures followed by an iterative refinement of the structural superposition. Systematic comparisons using benchmark datasets of MSTAs underlines that the alignment quality is better than MULTIPROT, MUSTANG and the alignments in HOMSTRAD, in more than 85% of the cases. Comparison with other rigid-body and flexible MSTAs also indicate that mulPBA alignments are superior to most of the rigid-body MSTAs and highly comparable to the flexible alignment methods. (C) 2012 Elsevier Masson SAS. All rights reserved.

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Carbon footprint (CF) refers to the total amount of carbon dioxide and its equivalents emitted due to various anthropogenic activities. Carbon emission and sequestration inventories have been reviewed sector-wise for all federal states in India to identify the sectors and regions responsible for carbon imbalances. This would help in implementing appropriate climate change mitigation and management strategies at disaggregated levels. Major sectors of carbon emissions in India are through electricity generation, transport, domestic energy consumption, industries and agriculture. A majority of carbon storage occurs in forest biomass and soil. This paper focuses on the statewise carbon emissions (CO2. CO and CH4), using region specific emission factors and statewise carbon sequestration capacity. The estimate shows that CO2, CO and CH4 emissions from India are 965.9, 22.5 and 16.9 Tg per year, respectively. Electricity generation contributes 35.5% of total CO2 emission, which is followed by the contribution from transport. Vehicular transport exclusively contributes 25.5% of total emission. The analysis shows that Maharashtra emits higher CO2, followed by Andhra Pradesh, Uttar Pradesh, Gujarat, Tamil Nadu and West Bengal. The carbon status, which is the ratio of annual carbon storage against carbon emission, for each federal state is computed. This shows that small states and union territories (UT) like Arunachal Pradesh, Mizoram and Andaman and Nicobar Islands, where carbon sequestration is higher due to good vegetation cover, have carbon status > 1. Annually, 7.35% of total carbon emissions get stored either in forest biomass or soil, out of which 34% is in Arunachal Pradesh, Madhya Pradesh, Chhattisgarh and Orissa. (C) 2012 Elsevier Ltd. All rights reserved.

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Single-layer graphene (SLG), the 3.4 angstrom thick two-dimensional sheet of sp(2) carbon atoms, was first prepared in 2004 by mechanical exfoliation of graphite crystals using the scotch tape technique. Since then, SLG has been prepared by other physical methods such as laser irradiation or ultrasonication of graphite in liquid media. Chemical methods of synthesis of SLG are more commonly used; the most popular involves preparation of single-layer graphene oxide followed by reduction with a stable reagent, often assisted by microwave heating. This method yields single-layer reduced graphene oxide. Other methods for preparing SLG include chemical vapour deposition over surfaces of transition metals such as Ni and Cu. Large-area SLG has also been prepared by epitaxial growth over SIC. Few-layer graphene (FLG) is prepared by several methods; arc discharge of graphite in hydrogen atmosphere being the most convenient. Several other methods for preparing FLG include exfoliation of graphite oxide by rapid heating, ultrasonication or laser irradiation of graphite in liquid media, reduction of few-layer graphene oxide, alkali metal intercalation followed by exfoliation. Graphene nanoribbons, which are rectangular strips of graphene, are best prepared by the unzipping of carbon nanotubes by chemical oxidation or laser irradiation. Many graphene analogues of inorganic materials such as MoS2, MoSe2 and BN have been prepared by mechanical exfoliation, ultrasonication and by chemical methods involving high-temperature or hydrothermal reactions and intercalation of alkali metals followed by exfoliation. Scrolls of graphene are prepared by potassium intercalation in graphite or by microwave irradiation of graphite immersed in liquid nitrogen.

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This article considers a class of deploy and search strategies for multi-robot systems and evaluates their performance. The application framework used is deployment of a system of autonomous mobile robots equipped with required sensors in a search space to gather information. The lack of information about the search space is modelled as an uncertainty density distribution. The agents are deployed to maximise single-step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for sequential deploy and search (SDS) and combined deploy and search (CDS) strategies. Completeness results are provided for both search strategies. The deployment strategy is analysed in the presence of constraints on robot speed and limit on sensor range for the convergence of trajectories with corresponding control laws responsible for the motion of robots. SDS and CDS strategies are compared with standard greedy and random search strategies on the basis of time taken to achieve reduction in the uncertainty density below a desired level. The simulation experiments reveal several important issues related to the dependence of the relative performances of the search strategies on parameters such as the number of robots, speed of robots and their sensor range limits.

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In this paper, we develop a game theoretic approach for clustering features in a learning problem. Feature clustering can serve as an important preprocessing step in many problems such as feature selection, dimensionality reduction, etc. In this approach, we view features as rational players of a coalitional game where they form coalitions (or clusters) among themselves in order to maximize their individual payoffs. We show how Nash Stable Partition (NSP), a well known concept in the coalitional game theory, provides a natural way of clustering features. Through this approach, one can obtain some desirable properties of the clusters by choosing appropriate payoff functions. For a small number of features, the NSP based clustering can be found by solving an integer linear program (ILP). However, for large number of features, the ILP based approach does not scale well and hence we propose a hierarchical approach. Interestingly, a key result that we prove on the equivalence between a k-size NSP of a coalitional game and minimum k-cut of an appropriately constructed graph comes in handy for large scale problems. In this paper, we use feature selection problem (in a classification setting) as a running example to illustrate our approach. We conduct experiments to illustrate the efficacy of our approach.