Description
Book Synopsis.- Evolutionary machine learning.
.- Social Interpretable Reinforcement Learning.
.- Into the Black Box: Mining Variable Importance with XAI.
.- Evolving RNNs for Stock Forecasting: A Low Parameter Efficient Alternative to Transformers.
.- Generate more than one child in your co-evolutionary semi-supervised learning GAN.
.- EDCA – An Evolutionary Data-Centric AutoML Framework for Efficient Pipelines.
.- 30 years of particle swarm optimisation.
.- Proposal of Efficient Particle Swarm Optimization for Constrained Optimization Problems.
.- A Survey of Modern Hybrid Particle Swarm Optimization Algorithms.
.- An Investigation of Structural Bias in Particle Swarm Optimization.
.- GPSO in PTO.
.- We are Sending you Back... to the Optimum! Fuzzy Time Travel Particle Swarm Optimization.
.- Memetic Variations of Overlapping Swarm Intelligence.
.- Analysis of Evolutionary Computation Methods: Theory, Empirics, and Real-World Applications.
.- Multi-Tree Genetic Programming for Large-scale Dynamic Tugboat Scheduling.
.- Bio-inspired Algorithms for Green Computing and Sustainable Complex Systems.
.- Hybridization of techniques based on Genetic Algorithms and Neural Networks to determine the water requirements of fig trees.
.- Evaluating the Impact of Hysteretic Phenomena and Implementation Choices on Energy Consumption in Evolutionary Algorithms.
.- Measuring energy consumption of BBOB fitness functions.
.- Computational Intelligence for Sustainability.
.- A PSO-based MPPT with Dynamic Monitoring Reset for PV Systems.
.- An innovative approach for managing the water requirements of fig trees using artificial intelligence.
.- GPBus: Genetic Programming based Automated Machine Learning for Bus Delay Prediction.
.- Improving Fairness in Allocation of Emergency Medical Services using Multi-Objective Evolutionary Optimization.
.- A Multi-Agent System for Optimal Train Scheduling in Single-Track Railways.
.- EvoLLMs (Integrating Evolutionary Computing with Large Language Models (LLMs).
.- Evolutionary Bias Identification with Embeddings.
.- Probing LLMs on Optimization Problems: Can They Recall and Interpret Problem Features?.
.- Open and Closed-source Models for LLM-generated Metaheuristics Solving Engineering Optimization Problem.
.- Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing.
.- Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms.
.- Evolutionary Computation in Edge, Fog, and Cloud Computing.
.- A Communication-aware and Energy-efficient Genetic Programming based Method for Dynamic Resource Allocation in Clouds.
.- A Genetic Algorithm-Based Parameter Selection for Communication Efficient Federated Learning.
.- Evolutionary Computation in Image Analysis, Signal Processing, and Pattern Recognition.
.- Evolving Cellular Automata with Function-Based Conditional Rules for Image Filtering.
.- Machine Learning and AI in Digital Healthcare and Personalized Medicine.
.- Addressing Radiotherapy Scheduling with a Bin Packing Problem Formulation: A Comparative Study of Exact Solvers and Genetic Algorithms.
.- A Symbolic Regression Screening Approach within Peptide Optimisation.
.- Estimation of total body fat using symbolic regression and evolutionary algorithms.
.- Soft Computing Applied to Games.
.- Injecting Combinatorial Optimization into MCTS: Application to the Board Game boop.
.- Robust search for the underlying objectives in black-box games with binary outcomes.
