SCOPE

Considered a subfield of computational intelligence focused on combinatorial optimisation problems, evolutionary computation is associated with systems that use computational models of evolutionary processes as the key elements in design and implementation, i.e. computational techniques which are based to some degree on the evolution of biological life in the natural world. A number of evolutionary computational models have been proposed, including evolutionary algorithms, genetic algorithms, the evolution strategy, evolutionary programming and swarm intelligence. These techniques form the basis of several disciplines such as artificial life and evolutionary robotics.

This conference intends to be a major forum for scientists, engineers and practitioners interested in the study, analysis, design, modeling and implementation of evolvable systems, both theoretically and in a broad range of application fields. ECTA welcomes both theoretical research and practical applications.

The conference also aims to foster hybrid approaches within evolutionary computation and also involving fuzzy computation and neural computation.

CONFERENCE TOPICS

    Memetic Algorithms
    Evolutionary Search and Meta-Heuristics
    Representation Techniques
    Co-Evolution and Collective Behavior
    Genetic Algorithms
    Evolutionary Multi-Objective Optimization
    Swarm/Collective Intelligence
    Ant Colony Optimization
    Evolutionary Learning Systems
    Evolvable/Adaptive Hardware and Systems
    Applications: Games and Entertainment Technologies, Evolutionary Robotics, Evolutionary Art and Design, Industrial and Real World Applications, Computational Economics and Finance
    Hyperheuristics
    Bio-inspired Metaheuristics
    Genetic Programming
    Hybrid Neuro/Genetic, Fuzzy/Genetic Systems
    Evolutionary Algorithm Configuration (EA for AutoML)
    Behavior Analysis of Evolutionary Algorithms
    Theory of Evolutionary Algorithms