AIxIA 2024 - Advances in Artificial Intelligence

This book constitutes the refereed proceedings of the XXIIIrd International Conference on AIxIA 2024 Advances in Artificial Intelligence, AIxIA 2024, held in Bolzano, Italy, during November 2528, 2024.

The 24 full papers and 1 invited paper included in this volume were carefully reviewed and selected from 41 submissions. The papers cover the following topics: artificial intelligence; journals; Natural Language Processing, Machine Learning, Hybrid AI and Applications of AI.

Inhalt

.- Against the Clock: Lessons Learned by Applying Temporal Planning in
Practice.

.- A Novel Approach for Leveraging Agent-based Experts on Large
Language Models to Enable Data Sharing among Heterogeneous IoT
Devices in Agriculture.

.- An Extensive Empirical Analysis of Macro-Actions for Numeric Planning.

.- Feature selection on contextual embedding pushing the sparseness.

.- Neuro-symbolic Integration for Open Set Recognition in Network
Intrusion Detection.

.- MM-IGLU-IT: Multi-Modal Interactive Grounded Language
Understanding in Italian.

.- IDADA: A Blended Inductive-Deductive Approach for Data Augmentation .

.- HaWANet: Road Scene Understanding with Multi-modal Sensor Data
using Height-Width-driven Attention Network.

.- Hybrid Classification of European Legislation using Sustainable
Development Goals.

.- Supporting Decision-Making for City Management through Automated
Planning and Execution.

.- NutriWell: an Explainable Ontology-Based FoodAI Service for
Nutrition and Health Management.

.- Regular Clocks for Temporal Task Specifications in Reinforcement
Learning.

.- A Real-Time Support with Haptic Feedback for Safer Driving using
Monocular Camera.

.- Relating explanations with the inductive biases of Deep Graph Networks.

.- ntegrating Temporal Planning and Knowledge Representation to
Generate Personalized Touristic Itineraries.

.- ASR Systems Under Acoustic Challenges: A Multilingual Study.

.- Automating Resume Analysis: Knowledge Graphs via Prompt Engineering.

.- Combined Text-Visual Attention Models for Robot Task Learning and
Execution.

.- ICE: An Evaluation Metric to Assess Symbolic Knowledge Quality.

.- Hierarchical Knowledge Extraction from Opaque Machine Learning
Predictors.

.- On Different Symbolic Music Representations for Algorithmic
Composition Approaches based on Neural Sequence Models.

.- DR-Minerva: a Multimodal Language Model based on Minerva for
Diagnostic Information Retrieval .

.- REPAIR platform: Robot-aidEd PersonAlIzed Rehabilitation.

.- Integrating classical planners with GPT-based Planning Policies.

.- Probabilistic Traces in Declarative Process Mining.