Penousal Machado

All the Truth About NEvAr

The use of Evolutionary Computation approaches to generate images has reached a great popularity. This led to the emergence of a new art form—Evolutionary Art—and to the proliferation of Evolutionary Art Tools. In this paper, we present an Evolutionary Art Tool, NEvAr, the experimental results achieved, and the work methodology used to generate images. In NEvAr, useful individuals are stored in a database in order to allow their reuse. This database is playing an increasingly important role in the creation of new images, which led us to the development of automatic seeding procedures, also described. The automation of fitness assignment is one of our present research interests. We will, therefore, describe some preliminary results achieved with our current approach to automatic evaluation.

GVR: A New Genetic Representation for the Vehicle Routing Problem

In this paper we analyse a new evolutionary approach to the vehicle routing problem. We present Genetic Vehicle Representation (GVR), a two-level representational scheme designed to deal in an effective way with all the information that candidate solutions must encode. Experimental results show that this method is both effective and robust, allowing the discovery of new best solutions for some well-known benchmarks.

Adaptive Critics for Evolutionary Artists

We focus on the development of artificial art critics. These systems analyze artworks, extracting relevant features, and produce an evaluation of the perceived pieces. The ability to perform aesthetic judgments is a desirable characteristic in an evolutionary artificial artist. As such, the inclusion of artificial art critics in these systems may improve their artistic abilities. We propose artificial art critics for the domains of music and visual arts, presenting a comprehensive set of experiments in author identification tasks. The experimental results show the viability and potential of our approach.

On the influence of GVR in vehicle routing

A comparative study is made between a new evolutionary approach for the Vehicle Routing Problem (VRP) and a standard evolutionary model, based on Path Representation. Genetic Vehicle Representation (GVR) is the new two-level representational scheme designed to deal in an effective way with all the information needed by candidate solutions. Experimental results, obtained from a set of VRP instances, show performance improvements when GVR is used.

Partially interactive evolutionary artists

User fatigue is probably the most pressing problem in current Interactive Evolutionary Computation systems. To address it we propose the use of automatic seeding procedure, phenotype filters, and partial automation fitness assignment. We test this approaches in the visual arts domain. To further enhance interactive evolution applications in aesthetic domains, we propose the use of artificial art critics—systems that perform stylistic and aesthetic valuations of art—presenting experimental results.

On the Evolution of Evolutionary Algorithms

In this paper we discuss the evolution of several components of a traditional Evolutionary Algorithm, such as genotype to phenotype mappings and genetic operators, presenting a formalized description of how this can be attained. We then focus on the evolution of mapping functions, for which we present experimental results achieved with a meta-evolutionary scheme.

Experiments in Computational Aesthetics

A novel approach to the production of evolutionary art is presented. This approach is based on the promotion of an arms race between an adaptive classifier and an evolutionary computation system. An artificial neural network is trained to discriminate among images previously created by the evolutionary engine and famous paintings. Once training is over, evolutionary computation is used to generate images that the neural network classifies as paintings. The images created throughout the evolutionary run are added to the training set and the process is repeated. This iterative process leads to the refinement of the classifier and forces the evolutionary algorithm to explore new paths. The experimental results attained across iterations are presented and analyzed. Validation tests were conducted in order to assess the changes induced by the refinement of the classifier and to identify the types of images that are difficult to classify. Taken as a whole, the experimental results show the soundness and potential of the proposed approach.

On the development of critics in evolutionary computation artists

One of the problems in the use of evolutionary computer systems in artistic tasks is the lack of artificial models of human critics. In this paper, based on the state of the art and on our previous related work, we propose a general architecture for an artificial art critic, and a strategy for the validation of this type of system. The architecture includes two modules: the analyser, which does a pre-processing of the artwork, extracting several measurements and characteristics; and the evaluator, which, based on the output of the analyser, classifies the artwork according to a certain criteria. The validation procedure consists of several stages, ranging from author and style discrimination to the integration of critic in a dynamic environment together with humans.

Evolutionary and Biologically Inspired Music, Sound, Art and Design

Generative Music with Stochastic Diffusion Search.- Music with Unconventional Computing: Towards a Step Sequencer from Plasmodium of Physarum Polycephalum.- Feature Discovery by Deep Learning for Aesthetic Analysis of Evolved Abstract Images.- FuXi: A Fish-Driven Instrument for Real-Time Music Performance.- Chorale Music Splicing System: An Algorithmic Music Composer Inspired by Molecular Splicing.- Towards an Evolutionary Computational Approach to Articulatory Vocal Synthesis with PRAAT.- The Sound Digestive System: A Strategy for Music and Sound Composition.- Avoidance Drawings Evolved Using Virtual Drawing Robots.- A Genetic Programming Approach to Generating Musical Compositions.- AudioInSpace: Exploring the Creative Fusion of Generative Audio, Visuals and Gameplay.- Toward Certain Sonic Properties of an Audio Feedback System by Evolutionary Control of Second-Order Structures.- Echo.- Evotype: Evolutionary Type Design.- Interior Illumination Design Using Genetic Programming.- Lichtsuchende: Exploring the Emergence of a Cybernetic Society.- Automatic Generation of Chord Progressions with an Artificial Immune System.- Evolving Diverse Design Populations Using Fitness Sharing and Random Forest Based Fitness Approximation.- Moody Music Generator: Characterising Control Parameters Using Crowdsourcing.- Schemographe: Application for a New Representation Technique and Methodology of Analysis in Tonal Harmony.- Biological Content Generation: Evolving Game Terrains Through Living Organisms.- Interpretability of Music Classification as a Criterion for Evolutionary Multi-objective Feature Selection.- On the Stylistic Evolution of a Society of Virtual Melody Composers.- DrawCompileEvolve: Sparking Interactive Evolutionary Art with Human Creations.

An Inverted Ant Colony Optimization approach to traffic

With an ever increasing number of vehicles traveling the roads, traffic problems such as congestions and increased travel times became a hot topic in the research community, and several approaches have been proposed to improve the performance of the traffic networks.This paper introduces the Inverted Ant Colony Optimization (IACO) algorithm, a variation of the classic Ant Colony algorithm that inverts its logic by converting the attraction of ants towards pheromones into a repulsion effect. IACO is then used in a decentralized traffic management system, where drivers become ants that deposit pheromones on the followed paths; they are then repelled by the pheromone scent, thus avoiding congested roads, and distributing the traffic through the network.Using SUMO (Simulation of Urban MObility), several experiments were conducted to compare the effects of using IACO with a shortest time algorithm in artificial and real world scenarios - using the map of a real city, and corresponding traffic data.The effect of the behavior caused by this algorithm is a decrease in traffic density in widely used roads, leading to improvements on the traffic network at a local and global level, decreasing trip time for drivers that adhere to the suggestions made by IACO as well as for those who do not. Considering different degrees of adhesion to the algorithm, IACO has significant advantages over the shortest time algorithm, improving overall network performance by decreasing trip times for both IACO-compliant vehicles (up to 84%) and remaining vehicles (up to 71%). Thus, it benefits individual drivers, promoting the adoption of IACO, and also the global road network. Furthermore, fuel consumption and CO2 emissions from both vehicle types decrease significantly when using IACO (up to 49%).