Bioinspired Optimization Methods and Their Applications

Bioinspired Optimization Methods and Their Applications

10th International Conference, BIOMA 2022, Maribor, Slovenia, November 17-18, 2022, Proceedings

Eftimov, Tome; Crepinsek, Matej; Mernik, Marjan

Springer International Publishing AG

11/2022

277

Mole

Inglês

9783031210938

15 a 20 dias

444

Descrição não disponível.
An agent-based model to investigate different behaviours in a crowd simulation.- Accelerating Evolutionary Neural Architecture Search for Remaining Useful Life Prediction.- ACOCaRS: Ant Colony Optimization Algorithm for Traveling Car Renter Problem.- A new type of anomaly detection problem in dynamic graphs: An ant colony optimization approach.- CSS- A Cheap-Surrogate-based Selection Operator for Multi-objective Optimization.- Empirical Similarity Measure for Metaheuristics.- Evaluation of Parallel Hierarchical Differential Evolution for Min-Max Optimization Problems Using SciPy.- Explaining Differential Evolution Performance Through Problem Landscape Characteristics.- Genetic improvement of TCP congestion avoidance.- Hybrid Acquisition Processes in Surrogate-based Optimization. Application to Covid-19 Contact Reduction.- Investigating the Impact of Independent Rule Fitnesses in a Learning Classifier System.- Modified Football Game Algorithm for Multimodal Optimization of Test TaskScheduling Problems Using Normalized Factor Random Key Encoding Scheme.- Performance Analysis of Selected Evolutionary Algorithms.- Refining Mutation Variants in Cartesian Genetic Programming.- Slime mould algorithm: An experimental study of nature-inspired optimizer.- SMOTE inspired extension for differential evolution.- The Influence of Local Search over Genetic Algorithms with Balanced Representations.- Trade-off of networks on weighted space analyzed via a method mimicking human walking track superposition.- Towards interpretable policies in multi-agent reinforcement learning tasksb.
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artificial intelligence;computer networks;computer programming;computer systems;correlation analysis;evolutionary algorithms;genetic algorithms;graph theory;machine learning;optimization problems;particle swarm optimization (pso);signal processing;swarm intelligence;theoretical computer science