Is swarm intelligence able to create mazes?

In this paper, the idea of applying Computational Intelligence in the process of creation board games, in particular mazes, is presented. For two different algorithms the proposed idea has been examined. The results of the experiments are shown and discussed to present advantages and disadvantages

Real-Time Cloud-based Game Management System via Cuckoo Search Algorithm

This paper analyses the idea of applying Swarm Intelligence in the process of managing the entire 2D board game in a real-time environment. For the proposed solution Game Management System is used as a cloud resource with a dedicated intelligent control agent. The described approach has been analysed on the basis of board games like mazes. The model and the control algorithm of the system is described and examined. The results of the experiments are presented and discussed to show possible advantages and disadvantages of the proposed method.

On Some Aspects of Genetic and Evolutionary Methods for Optimization Purposes

In this paper, the idea of applying Baldwin effect in a hybrid genetic algorithm with gradient local search is formulated. For two different test functions is examined proposed version of algorithm. Research results are presented and discussed to show potential efficiency of applied Baldwin effect

Simplified firefly algorithm for 2D image key-points search

In order to identify an object, human eyes firstly search the field of view for points or areas which have particular properties. These properties are used to recognise an image or an object. Then this process could be taken as a model to develop computer algorithms for images identification. This paper proposes the idea of applying the simplified firefly algorithm to search for key-areas in 2D images. For a set of input test images the proposed version of firefly algorithm has been examined. Research results are presented and discussed to show the efficiency of this evolutionary computation method.Comment: Published version on: 2014 IEEE Symposium on Computational Intelligence for Human-like Intelligenc

Toward adaptive heuristic video frames capturing and correction in real-time

Multimedia devices are widely used in professional applications as well as personal purposes. The use of computer vision systems enables detection and extraction of important features exposed in images. However constantly increasing demand for this type of video with high quality requires simple however reliable methods. The objective of presented research is to investigate applicability of heuristic method for real-time video frames capturing and correction

Fuzzy logic controller parameter optimization using metaheuristic Cuckoo search algorithm for a magnetic levitation system

The main benefits of fuzzy logic control (FLC) allow a qualitative knowledge of the desired system’s behavior to be included as IF-THEN linguistic rules for the control of dynamical systems where either an analytic model is not available or is too complex due, for instance, to the presence of nonlinear terms. The computational structure requires the definition of the FLC parameters namely, membership functions (MF) and a rule base (RB) defining the desired control policy. However, the optimization of the FLC parameters is generally carried out by means of a trial and error procedure or, more recently by using metaheuristic nature-inspired algorithms, for instance, particle swarm optimization, genetic algorithms, ant colony optimization, cuckoo search, etc. In this regard, the cuckoo search (CS) algorithm as one of the most promising and relatively recent developed nature-inspired algorithms, has been used to optimize FLC parameters in a limited variety of applications to determine the optimum FLC parameters of only the MF but not to the RB, as an extensive search in the literature has shown. In this paper, an optimization procedure based on the CS algorithm is presented to optimize all the parameters of the FLC, including the RB, and it is applied to a nonlinear magnetic levitation system. Comparative simulation results are provided to validate the features improvement of such an approach which can be extended to other FLC based control systems.Peer ReviewedPostprint (published version

On Optimal and Fair Service Allocation in Mobile Cloud Computing

This paper studies the optimal and fair service allocation for a variety of mobile applications (single or group and collaborative mobile applications) in mobile cloud computing. We exploit the observation that using tiered clouds, i.e. clouds at multiple levels (local and public) can increase the performance and scalability of mobile applications. We proposed a novel framework to model mobile applications as a location-time workflows (LTW) of tasks; here users mobility patterns are translated to mobile service usage patterns. We show that an optimal mapping of LTWs to tiered cloud resources considering multiple QoS goals such application delay, device power consumption and user cost/price is an NP-hard problem for both single and group-based applications. We propose an efficient heuristic algorithm called MuSIC that is able to perform well (73% of optimal, 30% better than simple strategies), and scale well to a large number of users while ensuring high mobile application QoS. We evaluate MuSIC and the 2-tier mobile cloud approach via implementation (on real world clouds) and extensive simulations using rich mobile applications like intensive signal processing, video streaming and multimedia file sharing applications. Our experimental and simulation results indicate that MuSIC supports scalable operation (100+ concurrent users executing complex workflows) while improving QoS. We observe about 25% lower delays and power (under fixed price constraints) and about 35% decrease in price (considering fixed delay) in comparison to only using the public cloud. Our studies also show that MuSIC performs quite well under different mobility patterns, e.g. random waypoint and Manhattan models

Synthèse de textures par l’exemple pour les applications interactives

Millions of individuals explore virtual worlds every day, for entertainment, training, or to plan business trips and vacations. Video games such as Eve Online, World of Warcraft, and many others popularized their existence. Sand boxes such as Minecraft and Second Life illustrated how they can serve as a media, letting people create, share and even sell their virtual productions. Navigation and exploration software such as Google Earth and Virtual Earth let us explore a virtual version of the real world, and let us enrich it with information shared between the millions of users using these services every day.Virtual environments are massive, dynamic 3D scenes, that are explored and manipulated interactively bythousands of users simultaneously. Many challenges have to be solved to achieve these goals. Among those lies the key question of content management. How can we create enough detailed graphical content so as to represent an immersive, convincing and coherent world? Even if we can produce this data, how can we then store the terra–bytes it represents, and transfer it for display to each individual users? Rich virtual environments require a massive amount of varied graphical content, so as to represent an immersive, convincing and coherent world. Creating this content is extremely time consuming for computer artists and requires a specific set of technical skills. Capturing the data from the real world can simplify this task but then requires a large quantity of storage, expensive hardware and long capture campaigns. While this is acceptable for important landmarks (e.g. the statue of Liberty in New York, the Eiffel tower in Paris) this is wasteful on generic or anonymous landscapes. In addition, in many cases capture is not an option, either because an imaginary scenery is required or because the scene to be represented no longer exists. Therefore, researchers have proposed methods to generate new content programmatically, using captured data as an example. Typically, building blocks are extracted from the example content and re–assembled to form new assets. Such approaches have been at the center of my research for the past ten years. However, algorithms for generating data programmatically only partially address the content management challenge: the algorithm generates content as a (slow) pre–process and its output has to be stored for later use. On the contrary, I have focused on proposing models and algorithms which can produce graphical content while minimizing storage. The content is either generated when it is needed for the current viewpoint, or is produced under a very compact form that can be later used for rendering. Thanks to such approaches developers gain time during content creation, but this also simplifies the distribution of the content by reducing the required data bandwidth.In addition to the core problem of content synthesis, my approaches required the development of new data-structures able to store sparse data generated during display, while enabling an efficient access. These data-structures are specialized for the massive parallelism of graphics processors. I contributed early in this domain and kept a constant focus on this area. The originality of my approach has thus been to consider simultaneously the problems of generating, storing and displaying the graphical content. As we shall see, each of these area involve different theoretical and technical backgrounds, that nicely complement each other in providing elegant solutions to content generation, management and display