![]() ![]() Modeling and analysis of new approaches.The ACO-SI Track welcomes submissions of original and unpublished work in all experimental and theoretical aspects of SI, including (but not limited to) the following areas: In the second category, SI has been successfully used to control large numbers of robots in a decentralized way, which increases the flexibility, robustness, and fault-tolerance of the resulting systems. In the first category, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) constitute two of the most popular SI optimization techniques with numerous applications in science and engineering. The two main application areas of SI have been optimization and robotics. Since these principles are observed in the organization of social insect colonies and other animal aggregates, such as bird flocks or fish schools, SI systems are typically inspired by these natural systems. ![]() SI systems rely on certain key principles such as decentralization, stigmergy, and self-organization. Swarm Intelligence (SI) is the collective problem-solving behavior of groups of animals or artificial agents that results from the local interactions of the individuals with each other and with their environment. GECH - General Evolutionary Computation and HybridsĪCO-SI - Ant Colony Optimization and Swarm Intelligence Description Three days of presentations of the latest high-quality results in 13 separate and independent program tracks specializing in various aspects of genetic and evolutionary computation.ĪCO-SI - Ant Colony Optimization and Swarm IntelligenceĬS - Complex Systems (Artificial Life/Artificial Immune Systems/Generative and Developmental Systems/Evolutionary Robotics/Evolvable Hardware)ĭETA - Digital Entertainment Technologies and ArtsĮCOM - Evolutionary Combinatorial Optimization and MetaheuristicsĮMO - Evolutionary Multiobjective OptimizationĮNUM - Evolutionary Numerical Optimization ![]()
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