This book constitutes the refereed proceedings of the 18th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2023, held in Salamanca, Spain, during September 5-7, 2023.
The 65 full papers included in this book were carefully reviewed and selected from 120 submissions. They were organized in topical sections as follows: ​Anomaly and Fault Detection, Data Mining and Decision Support Systems, Deep Learning, Evolutionary Computation and Optimization, HAIS Applications, Image and Speech Signal Processing, Agents and Multiagents, Biomedical Applicatons.

Table of Contents:
Anomaly and Fault Detection.- One-Class Reconstruction Methods for Categorizing DoS Attacks on CoAP.- Application of anomaly detection models to malware detection in the presence of concept drift.- Identification of anomalies in urban sound data with Autoencoders.- Revisiting Histogram Based Outlier Scores: Strengths and Weaknesses.- Data Mining and Decision Support Systems.- Model performance prediction: a Meta-Learning approach for concept drift detection.- Reinforcing Assessment Processes Using Proactive Case-Based Reasoning Mechanisms.- Meta-Learning for hyperparameters tuning in CNNs for Chest Images.- A Fuzzy Logic Ensemble Approach to Concept Drift Detection.- Multi-Task Gradient Boosting.- Exploratory Study of Data Sampling Methods for Imbalanced Legal Text Classification.- Exploring delay reduction on Edge Computing architectures from a Heuristic approach.- Probability Density Function for Clustering Validation.- Comprehensive analysis of different techniques for data augmentation and proposal of new variants of BOSME & GAN.- Multidimensional Models Supported by Document-Oriented Databases.- Financial Distress Prediction in an Imbalanced Data Stream Environment.- Improving the Quality of Quantum Services Generation Process: Controlling Errors and Noise.- Comparison of deep reinforcement learning path-following system based on road geometry and an adaptive cruise control for autonomous vehicles.- Deep Learning.- A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia.- Companion Classification Losses for Regression Problems.- Analysis of transformer model applications.- Real-time Workflow Scheduling in Cloud with Recursive Neural Network and List Scheduling.-  Robust Losses in Deep Regression.- Structure Learning in Deep Multi-Task Models.- Validating by Deep Learning an Efficient Method for Genomic Sequence Analysis: Genomic Spectrograms.- Sentiment Analysis for Vietnamese – Based Hybrid Deep Learning Models.- Optimizing LIME explanations using REVEL Metrics.- Assessing the Impact of Noise on Quantum Neural Networks: An Experimental Analysis.- Varroa mite detection using deep learning techniques.- Evolutionary Computation and Optimization.- Enhancing Evolutionary Optimization Performance under Byzantine Fault Conditions.- A hybrid based genetic algorithm for solving the clustered generalized traveling salesman problem.- Feature Ranking for Feature Sorting and Feature Selection with Optimisation.- Efficient Simulation of Pollutant Dispersion using Machine Learning.- Hybrid Intelligent Parsimony Search in Small High-dimensional Datasets.- An integer linear programming model for team formation in the classroom with constraints.- Improved Evolutionary Approach for Tuning Topic Models with Additive Regularization.- Time ofArrival error characterization for precise indoor localization of Autonomous Ground Vehicles.- Feature Selection based on a Decision Tree Genetic Algorithm.- Exact and Heuristic Lexicographic Methods for the Fuzzy Traveling Salesman Problem.- A Novel Genetic Algorithm with Specialized Genetic Operators for Clustering.- The Analysis of Hybrid Brain Storm Optimisation Approaches in Feature Selection.- HAIS Applications.- Supporting Emotion Recognition in Human-Robot Interactions: An Experimental Italian Textual Dataset.- Hybrid Intelligent Control for Maximum Power Point Tracking of a Floating Wind Turbine.- Statistical Dialog Tracking and Management for Task-oriented Conversational Systems.- A Causally Explainable Deep Learning Model with Modular Bayesian Network for Predicting Electric Energy Demand.- Using Large Language Models for Interpreting Autonomous Robots Behaviors.- Comparative analysis of intelligent techniques for categorization of the operational status of LiFePo4 batteries.- To Enhance Full-Text Biomedical Document Classification through Semantic Enrichment.- Predicting innovative cities using spatio-temporal activity patterns.- Daily accumulative photovoltaic energy prediction using hybrid intelligent model.- Comparison of geospatial trajectory clustering and feature trajectory clustering for public transportation trip data.- Image and Speech Signal Processing.- Adapting YOLOv8 as a vision-based animal detection system to facilitate herding.- Image classification understanding with Model Inspector tool.- Study on Synthetic Video Generation of Embryo Development.- Image reconstruction using Cellular Automata and Neural Networks.- Agents and Multiagents.- Monte-Carlo Tree Search for Multi-Agent Pathfinding: Preliminary Results.- The Problem of Concept Learning and Goals of Reasoning in Large Language Models.- Multi-AgentSystem for Multimodal Machine Learning Object Detection.- Biomedical Applicatons.- Convolutional Neural Networks for Diabetic Retinopathy Grading from iPhone Fundus Images.- Risk factors and survival after premature hospital readmission in frail subjects with delirium.- Generalizing an Improved GrowCut Algorithm for Mammography Lesion Detection.- Coherence of COVID-19 mortality of Spain versus western European countries.- A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma.- Analysis of Frequency Bands in Electroencephalograms for Automatic Detection of Photoparoxysmal Responses.- Textural and shape features for lesion classification in mammogram analysis.- Intent Recognition using Recurrent Neural Networks on Vital Sign Data: A Machine Learning Approach.