Complexity of Rational and Irrational Nash Equilibria

We introduce two new natural decision problems, denoted as ? RATIONAL NASH and ? IRRATIONAL NASH, pertinent to the rationality and irrationality, respectively, of Nash equilibria for (finite) strategic games. These problems ask, given a strategic game, whether or not it admits (i) a rational Nash equilibrium where all probabilities are rational numbers, and (ii) an irrational Nash equilibrium where at least one probability is irrational, respectively. We are interested here in the complexities of ? RATIONAL NASH and ? IRRATIONAL NASH. Towards this end, we study two other decision problems, denoted as NASH-EQUIVALENCE and NASH-REDUCTION, pertinent to some mutual properties of the sets of Nash equilibria of two given strategic games with the same number of players. The problem NASH-EQUIVALENCE asks whether or not the two sets of Nash equilibria coincide; we identify a restriction of its complementary problem that witnesses ? RATIONAL NASH. The problem NASH-REDUCTION asks whether or not there is a so called Nash reduction: a suitable map between corresponding strategy sets of players that yields a Nash equilibrium of the former game from a Nash equilibrium of the latter game; we identify a restriction of NASH-REDUCTION that witnesses ? IRRATIONAL NASH. As our main result, we provide two distinct reductions to simultaneously show that (i) NASH-EQUIVALENCE is co- $\mathcal{NP}$ -hard and ? RATIONAL NASH is $\mathcal{NP}$ -hard, and (ii) NASH-REDUCTION and ? IRRATIONAL NASH are both $\mathcal{NP}$ -hard, respectively. The reductions significantly extend techniques previously employed by Conitzer and Sandholm (Proceedings of the 18th Joint Conference on Artificial Intelligence, pp. 765–771, 2003; Games Econ. Behav. 63(2), 621–641, 2008).     

VERY STRONGLY CONSTRAINED PROBLEMS: AN ANT COLONY OPTIMIZATION APPROACH

Ant Colony Optimization (ACO) is a class of metaheuristic algorithms sharing the common approach of constructing a solution on the basis of information provided both by a standard constructive heuristic and by previously constructed solutions. This article is composed of three parts. The first one frames ACO in current trends of research on metaheuristics for combinatorial optimization. The second outlines some current research within the ACO community, reporting recent results obtained on different problems, while the third part focuses on a particular research line, named ANTS, providing some details on the algorithm and presenting results recently obtained on a prototypical strongly constrained problem: the set partitioning problem.     

Remote sensing of water quality in an Australian tropical freshwater impoundment using matrix inversion and MERIS images

The purpose of this study was to investigate how semi-analytical inversion techniques developed for the remote sensing of water quality parameters (chlorophyll a, tripton and coloured dissolved organic matter (CDOM)) in inland waters could be adapted or improved for application to Australian tropical and sub-tropical water bodies. The Matrix Inversion Method (MIM) with a semi-analytic model of the anisotropy of the in-water light field was applied to MERIS images of Burdekin Falls Dam, Australia, a tropical freshwater impoundment. Specific attention was required to improve the atmospheric correction of the MERIS data. The performance of the conventional three band exact solution of the MIM was compared to that of over-determined solutions that used constant and differential weighting for each sensor band.The results of the application of the MIM algorithm showed that the best weighting scheme had a mean chlorophyll a retrieval difference of 1.0 μgl^− 1, the three band direct matrix inversion scheme had a mean difference of 4.2 μgl^− 1 and the constant weight scheme had a mean difference of 5.5 μgl^− 1. For tripton, the best performed weighting scheme had a mean difference of 1.2 mgl^− 1, the three band scheme had a mean difference of 3.4 mgl^− 1 and the constant weight scheme had a mean difference of 1.8 mgl^− 1. For the CDOM retrieval, the mean difference was found to be 0.12 m^− 1 for the best performed weighting scheme, 0.25 m^− 1 for the three band scheme and 0.52 m^− 1 for the constant weight scheme. It was found that significant improvements in the accuracy and precision of retrieved water quality parameter values can be obtained by using differentially weighted, over-determined systems of equations, rather than exact solutions. These more reliable estimates of water quality parameters will allow water resource managers to improve their monitoring regimes.     

Graphical Congestion Games

We consider congestion games with linear latency functions in which each player is aware only of a subset of all the other players. This is modeled by means of a social knowledge graph G in which nodes represent players and there is an edge from i to j if i knows j. Under the assumption that the payoff of each player is affected only by the strategies of the adjacent ones, we first give a complete characterization of the games possessing pure Nash equilibria. Namely, if the social graph G is undirected, the game is an exact potential game and thus isomorphic to a classical congestion game. As a consequence, it always converges and possesses Nash equilibria. On the other hand, if G is directed an equilibrium is not guaranteed to exist, but the game is always convergent and an equilibrium can be found in polynomial time if G is acyclic, even if finding the best equilibrium remains an intractable problem.     

A physics based retrieval and quality assessment of bathymetry from suboptimal hyperspectral data

In order to retrieve bathymetry, substratum type and the concentrations of the optically active constituents of the water column, an integrated physics based mapping approach was applied to airborne hyperspectral data of Moreton Bay, Australia. The remotely sensed data were sub-optimal due to high and mid-level cloud covers. Critical to the correct interpretation of the resultant coastal bathymetry map was the development of a quality control procedure based on additional outputs of the integrated physics based mapping approach and the characteristics of the instrument. These two outputs were: an optical closure term which defines differences between the image and model based remote sensing signal; and an estimate of the relative contribution of the substratum signal to the remote sensing signal. This quality control procedure was able to identify those pixels with a reliable retrieval of depth and to detect thin and thick clouds and their shadows, which were subsequently masked out from further analysis. The derived coastal bathymetry in depths ranging 4-13 m for the mapped area was within ± 15% of boat-based multi-beam acoustic mapping survey of the same area. The agreement between the imaging spectrometry and the acoustic datasets varies as a function of the contribution of the bottom visibility to the remote sensing signal. As expected, there was greater agreement in shallower clear water (± 0.67 m) than quasi-optically deep water (± 1.35 m). The quantitative identification and screening of the optically deep waters and the quasi-optically deep waters led to improved precision in the depth retrieval. These results suggest that the physics based mapping approach adopted in this study performs well for retrieving water column depths in coastal waters in water depths ranging 4-13 m for the area and conditions studied, even with sub-optimal imagery.     

High-modal gain 1300-nm In(Ga)As-GaAs quantum-dot lasers

A semiconductor laser containing seven InAs-InGaAs stacked quantum-dot (QD) layers was grown by molecular beam epitaxy. Shallow mesa ridge-waveguide lasers with stripe width of 120 /spl mu/m were fabricated and tested. A high modal gain of 41 cm/sup -1/ was obtained at room temperature corresponding to a modal gain of /spl sim/6 cm/sup -1/ per QD layer, which is very promising to enable the realization of 1.3-/spl mu/m ultrashort cavity devices such as vertical-cavity surface-emitting lasers. Ground state laser action was achieved for a 360-/spl mu/m-cavity length with as-cleaved facets. The transparency current density per QD layer and internal quantum efficiency were 13 A/cm/sup 2/ and 67%, respectively.     

Human factor: the competitive advantage driver of the EU’s logistics sector

This article aims to test the weight that main sub-components of the global competitiveness index might have on the logistics performance index. We deploy a novel technique based on three newly particularised clusters (‘infrastructure’, ‘institutions’ and ‘human factor’) to look into whether such clusters are related to efficiency in the 28 European Union’s countries. It is manifest that the human factor is far more important for improving the logistics performance index than infrastructure and institutions. It follows that in this new domain of analysis, all initiatives to prioritise investment on the human factor are appropriate means of stimulating innovation and economic outlook, perceived that the logistics sector accounts for an average of 10% of the European Union’s GDP.     

Recent Progress on Metal-Based Nanomaterials: Fabrications,Optical Properties,and Applications in Ultrafast Photonics

Nanomaterials have demonstrated excellent mechanical, thermal, optical, and electrical properties in various fields, including 1D carbon nanotubes, as well as 2D materials starting from graphene. Metal-based nanomaterials, mainly divided into metal and metal oxide nanoparticles, also gradually come into the sight of ultrafast photonics applications due to the outstanding optical properties. The optical properties of metal nanoparticles can be enhanced by the interaction between conduction electrons with electric fields that is called surface plasmon resonance. As for metal oxide nanoparticles, optical properties are closely related to bandgap structures. When it comes to transition metal oxides, other phenomena also play important roles in optical absorption such as spin inversion and excitons of iron. Moreover, preparation methods of materials are also crucial for their properties and further applications. Therefore, in this review, commonly used physical and chemical fabrication methods for metal-based nanomaterials are first introduced. Then the optical properties of typical metal and metal oxide nanoparticles are discussed specifically. In addition, the applications of metal-based nanomaterials in ultrafast lasers based on mode-locked and Q-switched techniques are also summarized. Finally, a summary and outlook toward the synthesis, optical properties, and applications in ultrafast photonics of metal-based nanomaterials are presented.     

Design Rules for Laser‐Treated Icephobic Metallic Surfaces for Aeronautic Applications

Ice accretion on external aircraft surfaces due to the impact of supercooled water droplets can negatively affect the aerodynamic performance and reduce the operational capability and, therefore, must be prevented. Icephobic coatings capable of reducing the adhesion strength of ice to a surface represent a promising technology to support thermal or mechanical ice protection systems. Icephobicity is similar to hydrophobicity in several aspects and superhydrophobic surfaces embody a straightforward solution to the ice adhesion problem. Short/ultrashort pulsed laser surface treatments are proposed as a viable technology to generate superhydrophobic properties on metallic surfaces. However, it has not yet been verified whether such surfaces are generally icephobic under representative icing conditions. This study investigates the ice adhesion strength on Ti6Al4V, an alloy commonly used for aerospace components, textured by means of direct laser writing, direct laser interference patterning, and laser‐induced periodic surface structures laser sources with pulse durations ranging from nano‐ to femtosecond regimes. A clear relation between the spatial period, the surface microstructure depth, and the ice adhesion strength under different icing conditions is investigated. From these observations, a set of design rules can be defined for superhydrophobic surfaces that are icephobic, too.     

An approach for modeling and detecting software performance antipatterns based on first-order logics

The problem of interpreting the results of performance analysis is quite critical in the software performance domain. Mean values, variances and probability distributions are hard to interpret for providing feedback to software architects. Instead, what architects expect are solutions to performance problems, possibly in the form of architectural alternatives (e.g. split a software component in two components and re-deploy one of them). In a software performance engineering process, the path from analysis results to software design or implementation alternatives is still based on the skills and experience of analysts. In this paper, we propose an approach for the generation of feedback based on performance antipatterns. In particular, we focus on the representation and detection of antipatterns. To this goal, we model performance antipatterns as logical predicates and we build an engine, based on such predicates, aimed at detecting performance antipatterns in an XML representation of the software system. Finally, we show the approach at work on a case study.