Agents and Artificial Intelligence 15th International Conference, ICAART 2023, Lisbon, Portugal, February 22–24, 2023, Revised Selected Papers

This book contains the revised and extended versions of selected papers from the 15th International Conference on Agents and Artificial Intelligence, ICAART 2023, held in Lisbon, Portugal, during February 22–24, 2023.

The 23 full papers included in this book were carefully reviewed and selected from 306 submissions. The conference was organized in 2 tracks as follows:

One track focuses on Agents, Multi-Agent Systems and Software Platforms, Distributed Problem Solving and Distributed AI in general. The other track focuses mainly on Artificial Intelligence, Knowledge Representation, Planning, Learning, Scheduling, Perception Reactive AI Systems, and Evolutionary Computing and other topics related to Intelligent Systems and Computational Intelligence.

Agents.- Bees, Bats and Glowworms: Swarm Algorithms for Optimizing Industrial Plants from the Bottom-Up.- Estimating the Spread of COVID-19 Due to Transportation Networks Using Agent-Based Modeling.- Dealing with the Unpredictability of Physical Resources in Real-World Multi-Agent Systems.-  Coalition Alternating-Time Temporal Logic: A Logic to Find Good Coalitions to Achieve Strategic Objectives.- Holonic Energy Management Systems: Towards Flexible and Resilient Smart Grids.- Artificial Intelligence.- Predictive Explanations for and by Reinforcement Learning.- Effects of Feature Types on Donor Journey.- Data-Efficient Offline Reinforcement Learning with Approximate Symmetries.- Dynamic Communities: A Novel Recommendation Approach for Individuals and Groups.- Towards Improving Multivariate Time-Series Forecasting Using Weighted Linear Stacking.- Study on LSTM and ConvLSTM Memory-Based Deep Reinforcement Learning.- Spatial Representation and Reasoning About Fold Strata: A Qualitative Approach.- Ranking-Based Partner Selection Strategy in Open, Dynamic and Sociable Environments.- Weight Re-Mapping for Variational Quantum Algorithms.- Effective Adaptive Strategy Selection Using Extended Fine-Tuning and CNN-Based Surrogate Model in Repeated-Encounter Bilateral Automated Negotiation.- A Novel Bagged Ensemble Approach for Accurate Histopathological Breast Cancer Classification Using Transfer Learning and Convolutional Neural Networks.- UTP: A Unified Term Presentation Tool For Clinical Textual Data Using Pattern-Matching Rules and Dictionary-Based Ontologies.- Fault Tolerant Robust Adaptive Workload Orchestration in Pure Edge Computing.- Exploring Narrative Economics: An Agent-Based Co-Evolutionary Model Featuring Nonlinear Continuous-Time Opinion Dynamics.- GaSUME: A BERT-Covered Genetic Algorithm for Text Summarization.- Segmented Glioma Classification Using Radiomics-Based Machine Learning: A Comparative Analysis of Feature Selection Techniques.- RDC-Repair: Towards a Relevance-Driven Approach for Data and Constraints Repair.- Developing Image-Based Classification Techniques to Analyse Customer Behaviour.