Evolution Reinforces Cooperation with the Emergence of Self-Recognition Mechanisms: an empirical study of the Moran process for the iterated Prisoner's dilemma

We present insights and empirical results from an extensive numerical study of the evolutionary dynamics of the iterated prisoner's dilemma. Fixation probabilities for Moran processes are obtained for all pairs of 164 different strategies including classics such as TitForTat, zero determinant strategies, and many more sophisticated strategies. Players with long memories and sophisticated behaviours outperform many strategies that perform well in a two player setting. Moreover we introduce several strategies trained with evolutionary algorithms to excel at the Moran process. These strategies are excellent invaders and resistors of invasion and in some cases naturally evolve handshaking mechanisms to resist invasion. The best invaders were those trained to maximize total payoff while the best resistors invoke handshake mechanisms. This suggests that while maximizing individual payoff can lead to the evolution of cooperation through invasion, the relatively weak invasion resistance of payoff maximizing strategies are not as evolutionarily stable as strategies employing handshake mechanisms

Half a billion simulations: evolutionary algorithms and distributed computing for calibrating the SimpopLocal geographical model

Multi-agent geographical models integrate very large numbers of spatial interactions. In order to validate those models large amount of computing is necessary for their simulation and calibration. Here a new data processing chain including an automated calibration procedure is experimented on a computational grid using evolutionary algorithms. This is applied for the first time to a geographical model designed to simulate the evolution of an early urban settlement system. The method enables us to reduce the computing time and provides robust results. Using this method, we identify several parameter settings that minimise three objective functions that quantify how closely the model results match a reference pattern. As the values of each parameter in different settings are very close, this estimation considerably reduces the initial possible domain of variation of the parameters. The model is thus a useful tool for further multiple applications on empirical historical situations

A comparison of different evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem

The key problem in fractal image compression is that of obtaining the IFS code (a set of linear transformations)which approximates a given image with a certain prescribed accuracy (inverse IFS problem).In this paper,we analyze and compare the performance of sharing and crowding niching techniques for identifying optimal selfsimilar transformations likely to represent a selfsimilar area within the image. The best results are found using the deterministic crowding method.We also present an nteractive Matlab program implementing the algorithms described in the paper.The key problem in fractal image compression is that of obtaining the IFS code (a set of linear transformations)which approximates a given image with a certain prescribed accuracy (inverse IFS problem).In this paper,we analyze and compare the performance of sharing and crowding niching techniques for identifying optimal selfsimilar transformations likely to represent a selfsimilar area within the image. The best results are found using the deterministic crowding method.We also present an nteractive Matlab program implementing the algorithms described in the paper.Facultad de Informátic

A comparison of diferent evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem

The key problem in fractal image compression is that of obtaining the IFS code (a set of linear transformations) which approximates a given image with a certain prescribed accuracy (inverse IFS problem). In this paper, we analyze and compare the performance of sharing and crowding niching techniques for identifying optimal selfsimilar transformations likely to represent a selfsimilar area within the image. The best results are found using the deterministic crowding method. We also present an interactive Matlab program implementing the algorithms described in the paperI Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

An investigation into Quadtree fractal image and video compression

Digital imaging is the representation of drawings, photographs and pictures in a format that can be displayed and manipulated using a conventional computer. Digital imaging has enjoyed increasing popularity over recent years, with the explosion of digital photography, the Internet and graphics-intensive applications and games. Digitised images, like other digital media, require a relatively large amount of storage space. These storage requirements can become problematic as demands for higher resolution images increases and the resolution capabilities of digital cameras improve. It is not uncommon for a personal computer user to have a collection of thousands of digital images, mainly photographs, whilst the Internet’s Web pages present a practically infinite source. These two factors 一 image size and abundance 一 inevitably lead to a storage problem. As with other large files, data compression can help reduce these storage requirements. Data compression aims to reduce the overall storage requirements for a file by minimising redundancy. The most popular image compression method, JPEG, can reduce the storage requirements for a photographic image by a factor of ten whilst maintaining the appearance of the original image 一 or can deliver much greater levels of compression with a slight loss of quality as a trade-off. Whilst JPEG's efficiency has made it the definitive image compression algorithm, there is always a demand for even greater levels of compression and as a result new image compression techniques are constantly being explored. One such technique utilises the unique properties of Fractals. Fractals are relatively small mathematical formulae that can be used to generate abstract and often colourful images with infinite levels of detail. This property is of interest in the area of image compression because a detailed, high-resolution image can be represented by a few thousand bytes of formulae and coefficients rather than the more typical multi-megabyte filesizes. The real challenge associated with Fractal image compression is to determine the correct set of formulae and coefficients to represent the image a user is trying to compress; it is trivial to produce an image from a given formula but it is much, much harder to produce a formula from a given image. เท theory, Fractal compression can outperform JPEG for a given image and quality level, if the appropiate formulae can be determined. Fractal image compression can also be applied to digital video sequences, which are typically represented by a long series of digital images 一 or 'frames'