Overview

This three-volume set CCIS 2827-2829 constitutes the refereed proceedings of the 17th International Joint Conference on Computational Intelligence, IJCCI 2025, held in Marbella, Spain, during October 22–24, 2025. The 36 full papers and 83 short papers included in these volumes were carefully reviewed and selected from 146 submissions. They are organized into the following topical sections:  Part I: International Conference on Agentic and Generative Techniques in Intelligent Computational Systems; International Conference on Fuzzy Computation Theory and Applications. Part II: International Conference on Evolutionary Computation Theory and Applications. Part III: International Conference on Explainable AI for Neural and Symbolic Methods; International Conference on Neural Computation Theory and Applications.

Full Product Details

Author:   Francesco Marcelloni ,  Kurosh Madani ,  Niki van Stein ,  Joaquim Filipe
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
ISBN:  

9783032156372

ISBN 10:   3032156378
Pages:   781
Publication Date:   11 February 2026
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   Not yet available  
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Table of Contents

.- International Conference on Explainable AI for Neural and Symbolic Methods. .- AutoCausalAIME: A CMA-ES-Driven Framework for Parametric Penalty Tuning in Causal Inverse Explanations. .- Leveraging Large Language Models for Generating and Evaluating Natural Language Explanations in XAI: A Comparative Study. .- Uncertainty in Deep Model Performance for Radiology: A Case Study of Classifying Maxillary Sinus Appearance. .- Explain to Gain: Optimising Performance Through Explainable Reinforcement Learning Parameter Investigation. .- Quantifying Prototype Stability in ProtoPNet Without Manual Part Annotations. .- Interpretable Railway Object Classification Using Part-Prototype Networks. .- Efficient Construction of Interpretable Oblique Decision Trees. .- Extracting Deterministic Finite Automata from RNNs via Hyperplane Partitioning and Learning. .- Profiling German Text Simplification with Model-Fingerprints. .- Attention Maps in 3D Shape Classification for Dental Stage Estimation with Class Node Graph Attention Networks. .- Extensibility, Model Interpretability and Explainability, and Automation in ML.NET: A Comprehensive Analysis. .- SemantriX: An Explainable Hybrid Model for Aligning Vector Similarity and Semantic Relevance. .- Explainable Knowledge Access: Recursive and Rerank-Based RAG for Interpretable QA. .- How Prompting Shapes Decisions: Analyzing LLM Behavior in XAI-Augmented Decision Support Systems. .- Mechanistic Interpretability for Transformer-based Time Series Classification. .- XAI-Driven Solutions to Enhance Safety for Limited-Mobility Road Users. .- User Fairness in Recommender Systems using Beyond-Accuracy Basket Quality Metrics. .- Analyzing Accuracy and Consistency of GPT 4o Mini in Trivial Pursuit, and the Implications for its Use in Professional Contexts. .- Interpretable Explainable AI: Comparing Bayesian Structural Equation Modelling with Other Algorithms. .- Unsupervised Hierarchical Growing Neural Architecture for Sensorimotor Map Learning. .- Rule Extraction from Fake News Classifiers. .- Contrasting Human and Emergent Concepts in Image Classifiers. .- An Explainable Multi-Domain Document Summarization Framework using Domain-Aware Fine-Tuned Large Language Models. .- SPAX: A Shapley-Based Point Attribution eXplanation for Interpreting 3D Point Cloud Classification. .- A Privacy-Preserving and Explainable Approach for Anomaly Detection in Substation Networks. .- Exposing Shortcuts in Image Classification by Aggregating Counterfactuals. .- On Explainable Disease Progression Forecasting with Transformer Models. .- International Conference on Neural Computation Theory and Applications. .- Determining Optimal Pixel Resolution for Object Detection in Satellite Imagery: A Class-Specific Approach. .- Re-Ranked Transformer: New Strategy Based on Misspellings and Typos Pattern Analysis for Keystroke Biometrics Improvement. .- Towards Generalizing Deep Reinforcement Learning Algorithms for Real World Applications. .- Degradation-Aware Energy Management in Residential Microgrids: A Reinforcement Learning Framework. .- Innovative Techniques for Efficient Hyperdimensional Computing on Hardware: Enhance Accuracy and On-Fly Hypervector Generation. .- A Universal Urban Electricity-Demand Simulator for Developing and Evaluating Load-Scheduling and Forecasting Systems. .- Drowsiness Detection with Time-Series Classification Using HRV Features. .- A Structured Survey of Anomaly Types and Classification-Based Detection Models in IoT. .- Assessing Driving Style from Telematics Data with a Two-Stage Clustering Approach. .- Fine-Tuning Prototypes for Cross-Domain Few-Shot Image Classification Using Contrastive Objective. .- OS-QLR: One-Shot Quantized Latent Refinement for Fast and Efficient Image Generation. .- Dataset-Independent Approach for Generating Synthetic Data in Optical Defect Detection. .- Combining Large-Scale and Domain-Specific Datasets for Hate Speech Severity Modeling: A Regression-Based Approach. .- MLP Model for Prediction of Pellet Combustion: How to Deal with Small Datasets. .- Multi-Subspace SVD Generators for Continual Learning. .- From High-Frequency Sensors to Noon Reports: Using Transfer Learning for Shaft Power Prediction in Maritime. .- Towards Robust Urban Parking Violation Prediction Using Graph Kolmogorov–Arnold Networks and Liquid Neural Networks. .- Data Augmentation for Neuroaesthetics Analysis.

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