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[null,null,"Titolo",null,"Artificial Life and Evolutionary Computation : 17th Italian Workshop, WIVACE 2023, Venice, Italy, September 6–8, 2023, Revised Selected Papers / / edited by Marco Villani, Stefano Cagnoni, Roberto Serra"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"9783031574306"]
[{"$nulls":4},"3031574303"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (413 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science, , 1865-0937 ; ; 1977"]
[null,null,"Disciplina",null,"005.432"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Computer science - Mathematics"]
[{"$nulls":4},"Computer science"]
[{"$nulls":4},"Computer engineering"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Computers, Special purpose"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Mathematics of Computing"]
[{"$nulls":4},"Theory of Computation"]
[{"$nulls":4},"Computer Engineering and Networks"]
[{"$nulls":4},"Computer Communication Networks"]
[{"$nulls":4},"Special Purpose and Application-Based Systems"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- Algorithms for Complex Systems -- Energy Consumption of Evolutionary Algorithms in JavaScript -- 1 Introduction -- 2 State of the Art -- 3 Experimental Results -- 4 Conclusions -- References -- A Tabu Search Algorithm for the Map Labeling Problem -- 1 Introduction -- 2 The Map Labeling Problem -- 3 The Tabu Search Algorithm -- 4 Methodology -- 4.1 Solution Format -- 4.2 Label Placements Score -- 4.3 Neighbor Function -- 5 Results -- 6 Conclusions and Future Work -- References -- How to Turn a Leaky Learner into a Sealed One -- 1 Introduction -- 2 Methods -- 2.1 Motivation -- 2.2 Rényi's Matrix-Based Entropy Functional -- 2.3 Information Bottleneck Principle -- 3 "]
[{"$nulls":4},"Experiments -- 3.1 Data -- 3.2 Model -- 3.3 Initialization Schemes -- 4 Results -- 4.1 Consistency -- 4.2 Learning Dynamics of Both Learners -- 5 Discussion -- 5.1 Numerical Issues -- 5.2 Assessment and Further Investigation -- 6 Conclusion -- References -- Capturing Emerging Complexity in Lenia -- 1 Introduction -- 2 Lenia -- 3 Methodology -- 3.1 Variation over Time (VoT) Fitness -- 3.2 Autoencoder (AE) Based Fitness -- 3.3 Auto Encoder Variation over Time -- 4 Experimental Setup and Results -- 5 Conclusions -- References -- On the Detection of Significant Pairwise Interactions in Complex Systems -- 1 Introduction -- 2 The zI Index -- 3 The New Approach -- 4 Results -- 5 Conclusions -- Appendix A -- References -- Biologically Inspired Models -- The Properties of Pseudo-Attractors in Random Boolean Networks -- 1 Introduction -- 2 Simulation Results -- 3 Evolved Networks -- 4 Conclusions -- References -- Analysing the Expressiveness of Metabolic Networks Representations -- 1 Background -- 2 Methods -- 2.1 KEGG as a Source of Metabolic Data -- 2.2 Abstract Metabolic Networks, Reaction Graphs and Metabolic DAGs -- 2.3 Graph Kernels."]
[{"$nulls":4},"2.4 Data Visualisation and Analysis -- 3 Results and Discussion -- 3.1 Vertebrates Analysis -- 3.2 Mammals Analysis -- 3.3 Primates Analysis -- 4 Conclusion -- References -- scFBApy: A Python Framework for Super-Network Flux Balance Analysis -- 1 Introduction -- 1.1 State of the Art -- 1.2 Our Contribution -- 2 Material and Methods -- 2.1 Constraint-Based Modelling -- 2.2 From a Single-Network to a Super-Network -- 2.3 Transcriptomics-Derived Constraints to Metabolic Fluxes -- 2.4 Data Pre-processing -- 2.5 The ScFBApy Package -- 2.6 Datasets -- 2.7 The Metabolic Network Model -- 2.8 Experimental Setting -- 3 Experimental Results -- 3.1 Cooperation Between Cells Increases the Biomass Production -- 3.2 Cells Exchange Specific Metabolites to Increase the Biomass Production -- 3.3 Software Availability and Computational Architecture -- 4 Discussion and Conclusions -- References -- Semantic Information as a Measure of Synthetic Cells' Knowledge of the Environment -- 1 Introduction -- 2 Observed Semantic Information -- 3 Numerical Results -- 3.1 Evaluation of Viability and of Semantic Information -- 3.2 Normalization of pYt+1|Xt+1,Xt,Yt -- 4 Interpreting Semantic Information Values as a Measure of ``Knowledge'' SCs Have About Their Environment: A Preliminary Discussion -- 5 Conclusion -- References -- General Lines, Routes and Perspectives of Wetware Embodied AI. From Its Organizational Bases to a Glimpse on Social Chemical Robotics -- 1 Exorcizing the \"Ghost\" in the Machine -- 2 Wetware EAI -- 2.1 From EAI to \"Organismically-Inspired Robotics\", \"Enactive AI\" and Beyond: A Recap -- 2.2 Wetware EAI: The General Lines -- 2.3 Wetware Modeling of Life and Cognition -- 2.4 Autopoiesis and Autonomy -- 3 Social Robotics in the Chemical Domain -- 3.1 Social Robotics -- 3.2 Chemical Social Robotics -- 4 Concluding Remarks -- References."]
[{"$nulls":4},"A Proposed Mechanism for in vivo Programming Transmembrane Receptors -- 1 Introduction -- 2 Approach and Results -- 2.1 Relation Between Ligand Concentration and Number of Active Phosphorylation Sites -- 2.2 Application to G-Protein Coupled Receptors -- 3 Discussion -- References -- Complex Chemical Systems -- Kauffman Model with Spatially Separated Ligation and Cleavage Reactions -- 1 Introduction -- 2 Extension of the Kauffmann Model -- 2.1 ``In-Out'' Processes -- 2.2 Cleavage and Ligation Processes -- 2.3 Consideration of Finite Energy Amounts -- 2.4 Diffusion Processes -- 3 Simulation Details -- 4 Computational Results -- 4.1 Revisiting the Original Kauffman Model Within One Container Only -- 4.2 Two Separate "]
[{"$nulls":4},"Containers -- 4.3 Two Containers with Diffusion -- 4.4 Comparison of Final Dynamics -- 5 Conclusion and Outlook -- References -- Percolation Breakdown in Binary and Ternary Monodisperse and Polydisperse Systems of Spherical Particles -- 1 Introduction -- 2 Simulation Details -- 3 Network Analysis and Percolation Theory -- 4 Computational Results -- 5 Summary and Outlook -- References -- Adaptation and Swarms -- Entangled Gondolas. Design of Multi-layer Networks of Quantum-Driven Robotic Swarms -- 1 Introduction: The Core Idea -- 2 Novelties: Joining Swarm Robotics, Quantum Computing, and Multilayer Networks -- 2.1 A Quantum-Based Swarm of ``Telecommunicating'' Robots -- 2.2 Multilayer Networks to Model the Interactions Between Robots and Gondolas -- 2.3 Entanglement Between ``Gondolas'' -- 3 Discussion and Conclusions -- References -- Generalizations of Evolved Decision-Making Mechanisms in Swarm Collective Perception -- 1 Introduction -- 2 Related Work -- 3 Methods -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- An Investigation of Graceful Degradation in Boolean Network Robots Subject to Online Adaptation -- 1 Introduction."]
[{"$nulls":4},"2 Boolean Networks -- 3 Adaptation -- 4 Experimental Setting -- 5 Results -- 6 Conclusion -- References -- Blockchain-Empowered PSO for Scalable Swarm Robotics -- 1 Introduction -- 2 PSO in Swarm Robotics -- 3 Blockchain and the Tendermint System -- 4 Blockchain-Based PSO for Swarm Robotics -- 4.1 A Tendermint PSO Implementation -- 4.2 Asynchronous bPSO Implementation in Tendermint -- 4.3 Results and Evaluations -- 5 Conclusions -- References -- Hybrid GP/PSO Representation of 1-D Signals in an Autoencoder Fashion -- 1 Introduction -- 1.1 Genetic Programming and Latent Data Representations -- 1.2 Autoencoders -- 2 GP2SO: Symbolic Regression-Based Representation of Time-Dependent Signals -- 3 Implementation -- 3.1 Function and Terminal Set -- 3.2 Fitness Function -- 4 Proof of Concept -- 5 Possible Applications, Preliminary Tests, and Open Problems -- 6 Conclusions -- References -- Learning -- Local Delay Plasticity Supports Generalized Learning in Spiking Neural Networks -- 1 Introduction -- 2 Delay Learning in Spiking Neural Networks -- 2.1 Activity-Dependent Delay Plasticity -- 2.2 Encoding and Decoding with Spike Times -- 3 Proof-of-concept: Classification of Handwritten Digits -- 3.1 Experimental Setup -- 3.2 Delay Training Improves Classification Accuracy -- 3.3 Networks with Plastic Delays Generalized Training to an Unseen Input Class -- 3.4 Output Activity Patterns Before and After Training -- 4 Discussion -- 4.1 SNNs Can Be Trained with Local Delay Plasticity -- 4.2 Delay Plasticity Enables Generalized Learning -- 4.3 Competition in the Output Layers to Improve Separability -- 4.4 Future Work: Mixed-Mode Learning and Neuromorphics -- References -- Improving PVC Detection in ECG Signals: A Recurrent Neural Network Approach -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 Dataset -- 3.2 Residual Neural Network -- 3.3 EGA."]
[{"$nulls":4},"3.4 Map/Reduce Approach to Run EGA -- 3.5 Anomalies Detection -- 4 Results -- 5 Conclusions -- References -- Medicine -- Clustering Trajectories to Study Diabetic Kidney Disease -- 1 Introduction -- 2 Methodology -- 2.1 A Shape-Similarity Clustering of Longitudinal Data -- 2.2 Category Theory for Trajectory Clustering -- 2.3 Study Population -- 3 Results of the Longitudinal Clustering -- 4 Discussion -- References -- Multi-classification of Alzheimer's Disease by NSGA-II Slices Optimization and Fusion Deep Learning -- 1 Introduction -- 2 Cohort Used. ADNI Database -- 3 Methodology -- 3.1 Phase 1: Selecting the Best Slices in the X and Y Plane -- 3.2 Phase 2: Fusion Several Deep Learning System with Different Slices Selected -- 4 "]
[{"$nulls":4},"Results -- 5 Conclusion -- References -- Exploiting the Potential of Bayesian Networks in Deriving New Insight into Diabetic Kidney Disease (DKD) -- 1 Introduction -- 2 Materials and Methods -- 2.1 The PROVALID Study -- 2.2 The Bayesian Networks -- 3 Results -- 4 Concluding Remarks -- References -- A Genetic Algorithm for Feature Selection for Alzheimer's Disease Detection Using a Deep Transfer Learning Approach -- 1 Introduction -- 2 Data Acquisition -- 2.1 The Tasks -- 2.2 Image Generation -- 3 The Proposed Workflow -- 3.1 Deep Feature Extraction -- 3.2 Feature Selection -- 3.3 Grid Search and Classification -- 3.4 Majority Vote -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- Social Systems -- Learning Whether to be Informed in an Agent-Based Evolutionary Market Model -- 1 Introduction -- 2 The Model -- 3 Results -- 4 Conclusion -- References -- Heterogeneous Mean-Field Analysis of Best-of-n Decision Making in Networks with Zealots -- 1 Introduction -- 2 Method and Methodology -- 2.1 Model Description -- 2.2 A Mathematical Model with Option's Quality and Zealots."]
[{"$nulls":4},"2.3 Equilibria and Stability of the Analytical Model."]
[null,null,null,"Sommario/riassunto","This book constitutes the refereed post proceedings of the 17th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2023, held in Venice, Italy, during September 6–8, 2023. The 30 full papers included in this book were carefully reviewed and selected from 55 submissions. They were organized in topical sections as follows: Algorithms for complex systems, Biologically inspired models, Complex chemical systems, Adaptation and swarms, Learning, Medicine and Social systems."]