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Artificial Evolution [[electronic resource] ] : 13th International Conference, Évolution Artificielle, EA 2017, Paris, France, October 25–27, 2017, Revised Selected Papers / / edited by Evelyne Lutton, Pierrick Legrand, Pierre Parrend, Nicolas Monmarché, Marc Schoenauer
| Artificial Evolution [[electronic resource] ] : 13th International Conference, Évolution Artificielle, EA 2017, Paris, France, October 25–27, 2017, Revised Selected Papers / / edited by Evelyne Lutton, Pierrick Legrand, Pierre Parrend, Nicolas Monmarché, Marc Schoenauer |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XVI, 231 p. 77 illus.) |
| Disciplina | 005.1 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Artificial intelligence
Algorithms Computer science—Mathematics Discrete mathematics Numerical analysis Artificial Intelligence Discrete Mathematics in Computer Science Numerical Analysis Mathematical Applications in Computer Science |
| ISBN | 3-319-78133-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Évolution Artificielle 2017 - EA 2017 -- Abstracts of Invited Talks -- The Cartography of Computational Search Spaces -- Progressive Data Analysis: A New Computation Paradigm for Scalability in Exploratory Data Analysis -- Contents -- On the Design of a Master-Worker Adaptive Algorithm Selection Framework -- 1 Introduction -- 2 Related Works -- 2.1 Sequential Adaptive Algorithm Selection -- 2.2 Parallel Adaptive Algorithm Selection -- 2.3 Benchmarks: The Fitness Cloud Model -- 3 M/W Framework Description -- 3.1 Aggregation of Local Reward Values -- 3.2 Homogeneous vs. Heterogeneous Adaptive Selection -- 4 Experimental Analysis -- 4.1 Overall Relative Performance -- 4.2 Analysis of the Reward Aggregation Functions -- 4.3 Analysis of the Heterogeneity Scenarios -- 5 Conclusions -- References -- Comparison of Acceptance Criteria in Randomized Local Searches -- 1 Introduction -- 2 Literature Review -- 3 Experimental Setup -- 4 Experiments on the Quadratic Assignment Problem -- 5 Experiments on the Permutation Flow-Shop Problem -- 6 Conclusions -- References -- A Fitness Landscape View on the Tuning of an Asynchronous Master-Worker EA for Nuclear Reactor Design -- 1 Introduction -- 2 Preliminaries -- 2.1 Evolutionary Optimization for Nuclear Energy Problems -- 2.2 Parallel Evolutionary Algorithms -- 2.3 Landscape Aware Parameter Tuning -- 3 Problem Definition -- 3.1 Description of the System -- 3.2 Criterion of Interest -- 4 Asynchronous Parallel EA -- 4.1 Algorithm Definition -- 4.2 Mutation Operator -- 5 Experimental Analysis -- 5.1 Baseline Parameters Setting -- 5.2 Impact of the Mutation Parameters -- 5.3 Fitness Landscape Analysis -- 6 Conclusions -- References -- Sampled Walk and Binary Fitness Landscapes Exploration -- 1 Introduction -- 2 Fitness Landscapes -- 3 Partial Neighborhood Local Searches.
4 Analysis on Binary Fitness Landscapes -- 4.1 Experimental Protocol -- 4.2 Results -- 4.3 Landscapes Ruggedness and Partial Neighborhood LS Efficiency -- 5 Conclusion -- References -- Semantics-Based Crossover for Program Synthesis in Genetic Programming -- 1 Introduction -- 2 Related Work -- 2.1 Semantics -- 2.2 Semantic Crossover -- 3 Semantics in Program Synthesis -- 3.1 Semantic Similarity Measure with Traces -- 3.2 Semantic Crossover for Program Synthesis -- 4 Experimental Setup -- 4.1 Benchmark Problems -- 5 Results -- 5.1 Successful Runs and Fitness -- 5.2 Parent Comparison -- 5.3 Types Selected for Similarity Measurement -- 6 Conclusion and Future Work -- References -- On the Use of Dynamic GP Fitness Cases in Static and Dynamic Optimisation Problems -- 1 Introduction -- 2 Related Work -- 2.1 Fitness Cases in Genetic Programming -- 2.2 Promoting and Maintaining Diversity -- 3 Proposed Approaches -- 3.1 Dynamic Fitness Cases -- 3.2 Kendall Tau Distance -- 4 Experimental Setup -- 5 Results and Discussion -- 5.1 Performance on a Static Setting -- 5.2 Performance on a Dynamic Setting -- 5.3 Analysis of the Number of Created Individuals -- 5.4 Size of GP Programs -- 6 Conclusions -- References -- MEMSA: A Robust Parisian EA for Multidimensional Multiple Sequence Alignment -- 1 Introduction -- 1.1 Multiple Sequence Alignment (MSA) -- 1.2 Evolutionary Algorithms for MSA -- 1.3 Parisian Evolution Approach -- 2 Genetic Algorithm with Parisian Approach for MSA -- 2.1 Individuals/Patches -- 2.2 Initialisation -- 2.3 Crossover -- 2.4 Mutator -- 2.5 Evaluation -- 2.6 Diversity Preservation -- 2.7 Selection of Individuals for the New Generation -- 2.8 Patchwork to Create an MSA -- 2.9 Run Parameters and Behaviour of the Algorithm -- 3 Experiments and Validation -- 4 Discussion and Conclusion -- References. Basic, Dual, Adaptive, and Directed Mutation Operators in the Fly Algorithm -- 1 Introduction -- 2 Problem Definition and Motivations -- 3 Overview of the Fly Algorithm for PET Reconstruction -- 4 Varying Mutation Operators in the Fly Algorithm -- 4.1 Basic Mutation -- 4.2 Adaptive Mutation Variance -- 4.3 Dual Mutation -- 4.4 Directed Mutation -- 5 Results -- 6 Conclusion -- References -- A New High-Level Relay Hybrid Metaheuristic for Black-Box Optimization Problems -- 1 Introduction -- 2 Presentation of the Hybridized Components -- 2.1 Overview of MLSDO Algorithm -- 2.2 Overview of SHADE Algorithm -- 2.3 Overview of SPSO2011 Algorithm -- 3 The Proposed Hybrid Algorithm -- 4 Experimental Protocol and Parameter Setting -- 4.1 The BBOB 2015 Benchmark -- 4.2 The Black Box Optimization Competition -- 4.3 Parameter Setting -- 5 Experimental Results and Discussion -- 5.1 Results for the BBOB 2015 Benchmark -- 5.2 Results at the Black Box Optimization Competition -- 6 Conclusion -- References -- Improved Hybrid Iterative Tabu Search for QAP Using Distance Cooperation -- 1 Introduction -- 2 Background -- 3 Distributed and Cooperative Algorithms -- 3.1 Distributed Hybrid Iterative Tabu Search -- 3.2 Distance Cooperation Hybrid Iterative Tabu Search -- 4 Experimental Results -- 4.1 Platform and Tests -- 4.2 Parameters -- 4.3 Experimentation -- 4.4 Literature Comparison -- 5 Conclusion and Perspectives -- References -- H-ACO: A Heterogeneous Ant Colony Optimisation Approach with Application to the Travelling Salesman Problem -- 1 Introduction -- 2 Ant Colony Optimization -- 3 Heterogeneous ACO -- 4 Methodology -- 4.1 Travelling Salesman Problem bib2 -- 5 Experimental Setup -- 6 Heterogeneous ACO Results -- 6.1 Exploring the Ranges of Alpha and Beta -- 6.2 Comparison with Base Algorithms -- 7 Discussion, Conclusion and Future Work -- References. Evolutionary Learning of Fire Fighting Strategies -- 1 Introduction -- 2 Fire Enclosement in a Discrete Grid Setting -- 2.1 A Goal Oriented Evolution Model -- 2.2 Evolutionary Algorithm -- 2.3 Experimental Results -- 2.4 Fire Enclosement Conclusion -- 3 Protection of a Highway -- 3.1 Evolution Models -- 3.2 Evolutionary Algorithm -- 3.3 Experimental Results -- 3.4 Highway Protection Conclusion -- 4 Future Work on Theoretical Threshold Questions -- References -- Evolutionary Optimization of Tone Mapped Image Quality Index -- 1 Introduction -- 2 Related Work -- 3 Algorithm -- 3.1 Tone Mapping -- 3.2 Evolutionary Optimization -- 4 Experimental Results -- 5 Conclusion -- References -- LIDeOGraM: An Interactive Evolutionary Modelling Tool -- 1 Introduction -- 2 Background -- 2.1 Food Complex Systems -- 2.2 Symbolic Regression -- 2.3 Production and Stabilisation Process of Lactic Acid Bacteria -- 3 Proposed Approach -- 4 Experimental Results -- 4.1 The Dataset -- 4.2 Search with Eureqa -- 4.3 Optimisation of the Global Model -- 5 Discussion -- 6 Conclusions -- References -- Automatic Configuration of GCC Using Irace -- 1 Introduction -- 2 Automatic Algorithm Configuration -- 3 Configuration Scenarios -- 4 GCC Configuration Scenarios Analysis -- 5 Experimental Results -- 6 Conclusion and Future Work -- References -- Offline Learning for Selection Hyper-heuristics with Elman Networks -- 1 Introduction -- 2 Methodology -- 2.1 HyFlex and the Offline Learning Database -- 2.2 Final Log Returns and the BEST Sequences -- 2.3 Elman Networks -- 2.4 Training Sets -- 2.5 The BLIND Hyper-heuristic -- 3 Results -- 3.1 Network Training -- 3.2 Evaluating the Elman Network Sequences -- 4 Conclusions -- References -- Author Index. |
| Record Nr. | UNISA-996465520903316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Evolution [[electronic resource] ] : 13th International Conference, Évolution Artificielle, EA 2017, Paris, France, October 25–27, 2017, Revised Selected Papers / / edited by Evelyne Lutton, Pierrick Legrand, Pierre Parrend, Nicolas Monmarché, Marc Schoenauer
| Artificial Evolution [[electronic resource] ] : 13th International Conference, Évolution Artificielle, EA 2017, Paris, France, October 25–27, 2017, Revised Selected Papers / / edited by Evelyne Lutton, Pierrick Legrand, Pierre Parrend, Nicolas Monmarché, Marc Schoenauer |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XVI, 231 p. 77 illus.) |
| Disciplina | 005.1 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Artificial intelligence
Algorithms Computer science—Mathematics Discrete mathematics Numerical analysis Artificial Intelligence Discrete Mathematics in Computer Science Numerical Analysis Mathematical Applications in Computer Science |
| ISBN | 3-319-78133-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Évolution Artificielle 2017 - EA 2017 -- Abstracts of Invited Talks -- The Cartography of Computational Search Spaces -- Progressive Data Analysis: A New Computation Paradigm for Scalability in Exploratory Data Analysis -- Contents -- On the Design of a Master-Worker Adaptive Algorithm Selection Framework -- 1 Introduction -- 2 Related Works -- 2.1 Sequential Adaptive Algorithm Selection -- 2.2 Parallel Adaptive Algorithm Selection -- 2.3 Benchmarks: The Fitness Cloud Model -- 3 M/W Framework Description -- 3.1 Aggregation of Local Reward Values -- 3.2 Homogeneous vs. Heterogeneous Adaptive Selection -- 4 Experimental Analysis -- 4.1 Overall Relative Performance -- 4.2 Analysis of the Reward Aggregation Functions -- 4.3 Analysis of the Heterogeneity Scenarios -- 5 Conclusions -- References -- Comparison of Acceptance Criteria in Randomized Local Searches -- 1 Introduction -- 2 Literature Review -- 3 Experimental Setup -- 4 Experiments on the Quadratic Assignment Problem -- 5 Experiments on the Permutation Flow-Shop Problem -- 6 Conclusions -- References -- A Fitness Landscape View on the Tuning of an Asynchronous Master-Worker EA for Nuclear Reactor Design -- 1 Introduction -- 2 Preliminaries -- 2.1 Evolutionary Optimization for Nuclear Energy Problems -- 2.2 Parallel Evolutionary Algorithms -- 2.3 Landscape Aware Parameter Tuning -- 3 Problem Definition -- 3.1 Description of the System -- 3.2 Criterion of Interest -- 4 Asynchronous Parallel EA -- 4.1 Algorithm Definition -- 4.2 Mutation Operator -- 5 Experimental Analysis -- 5.1 Baseline Parameters Setting -- 5.2 Impact of the Mutation Parameters -- 5.3 Fitness Landscape Analysis -- 6 Conclusions -- References -- Sampled Walk and Binary Fitness Landscapes Exploration -- 1 Introduction -- 2 Fitness Landscapes -- 3 Partial Neighborhood Local Searches.
4 Analysis on Binary Fitness Landscapes -- 4.1 Experimental Protocol -- 4.2 Results -- 4.3 Landscapes Ruggedness and Partial Neighborhood LS Efficiency -- 5 Conclusion -- References -- Semantics-Based Crossover for Program Synthesis in Genetic Programming -- 1 Introduction -- 2 Related Work -- 2.1 Semantics -- 2.2 Semantic Crossover -- 3 Semantics in Program Synthesis -- 3.1 Semantic Similarity Measure with Traces -- 3.2 Semantic Crossover for Program Synthesis -- 4 Experimental Setup -- 4.1 Benchmark Problems -- 5 Results -- 5.1 Successful Runs and Fitness -- 5.2 Parent Comparison -- 5.3 Types Selected for Similarity Measurement -- 6 Conclusion and Future Work -- References -- On the Use of Dynamic GP Fitness Cases in Static and Dynamic Optimisation Problems -- 1 Introduction -- 2 Related Work -- 2.1 Fitness Cases in Genetic Programming -- 2.2 Promoting and Maintaining Diversity -- 3 Proposed Approaches -- 3.1 Dynamic Fitness Cases -- 3.2 Kendall Tau Distance -- 4 Experimental Setup -- 5 Results and Discussion -- 5.1 Performance on a Static Setting -- 5.2 Performance on a Dynamic Setting -- 5.3 Analysis of the Number of Created Individuals -- 5.4 Size of GP Programs -- 6 Conclusions -- References -- MEMSA: A Robust Parisian EA for Multidimensional Multiple Sequence Alignment -- 1 Introduction -- 1.1 Multiple Sequence Alignment (MSA) -- 1.2 Evolutionary Algorithms for MSA -- 1.3 Parisian Evolution Approach -- 2 Genetic Algorithm with Parisian Approach for MSA -- 2.1 Individuals/Patches -- 2.2 Initialisation -- 2.3 Crossover -- 2.4 Mutator -- 2.5 Evaluation -- 2.6 Diversity Preservation -- 2.7 Selection of Individuals for the New Generation -- 2.8 Patchwork to Create an MSA -- 2.9 Run Parameters and Behaviour of the Algorithm -- 3 Experiments and Validation -- 4 Discussion and Conclusion -- References. Basic, Dual, Adaptive, and Directed Mutation Operators in the Fly Algorithm -- 1 Introduction -- 2 Problem Definition and Motivations -- 3 Overview of the Fly Algorithm for PET Reconstruction -- 4 Varying Mutation Operators in the Fly Algorithm -- 4.1 Basic Mutation -- 4.2 Adaptive Mutation Variance -- 4.3 Dual Mutation -- 4.4 Directed Mutation -- 5 Results -- 6 Conclusion -- References -- A New High-Level Relay Hybrid Metaheuristic for Black-Box Optimization Problems -- 1 Introduction -- 2 Presentation of the Hybridized Components -- 2.1 Overview of MLSDO Algorithm -- 2.2 Overview of SHADE Algorithm -- 2.3 Overview of SPSO2011 Algorithm -- 3 The Proposed Hybrid Algorithm -- 4 Experimental Protocol and Parameter Setting -- 4.1 The BBOB 2015 Benchmark -- 4.2 The Black Box Optimization Competition -- 4.3 Parameter Setting -- 5 Experimental Results and Discussion -- 5.1 Results for the BBOB 2015 Benchmark -- 5.2 Results at the Black Box Optimization Competition -- 6 Conclusion -- References -- Improved Hybrid Iterative Tabu Search for QAP Using Distance Cooperation -- 1 Introduction -- 2 Background -- 3 Distributed and Cooperative Algorithms -- 3.1 Distributed Hybrid Iterative Tabu Search -- 3.2 Distance Cooperation Hybrid Iterative Tabu Search -- 4 Experimental Results -- 4.1 Platform and Tests -- 4.2 Parameters -- 4.3 Experimentation -- 4.4 Literature Comparison -- 5 Conclusion and Perspectives -- References -- H-ACO: A Heterogeneous Ant Colony Optimisation Approach with Application to the Travelling Salesman Problem -- 1 Introduction -- 2 Ant Colony Optimization -- 3 Heterogeneous ACO -- 4 Methodology -- 4.1 Travelling Salesman Problem bib2 -- 5 Experimental Setup -- 6 Heterogeneous ACO Results -- 6.1 Exploring the Ranges of Alpha and Beta -- 6.2 Comparison with Base Algorithms -- 7 Discussion, Conclusion and Future Work -- References. Evolutionary Learning of Fire Fighting Strategies -- 1 Introduction -- 2 Fire Enclosement in a Discrete Grid Setting -- 2.1 A Goal Oriented Evolution Model -- 2.2 Evolutionary Algorithm -- 2.3 Experimental Results -- 2.4 Fire Enclosement Conclusion -- 3 Protection of a Highway -- 3.1 Evolution Models -- 3.2 Evolutionary Algorithm -- 3.3 Experimental Results -- 3.4 Highway Protection Conclusion -- 4 Future Work on Theoretical Threshold Questions -- References -- Evolutionary Optimization of Tone Mapped Image Quality Index -- 1 Introduction -- 2 Related Work -- 3 Algorithm -- 3.1 Tone Mapping -- 3.2 Evolutionary Optimization -- 4 Experimental Results -- 5 Conclusion -- References -- LIDeOGraM: An Interactive Evolutionary Modelling Tool -- 1 Introduction -- 2 Background -- 2.1 Food Complex Systems -- 2.2 Symbolic Regression -- 2.3 Production and Stabilisation Process of Lactic Acid Bacteria -- 3 Proposed Approach -- 4 Experimental Results -- 4.1 The Dataset -- 4.2 Search with Eureqa -- 4.3 Optimisation of the Global Model -- 5 Discussion -- 6 Conclusions -- References -- Automatic Configuration of GCC Using Irace -- 1 Introduction -- 2 Automatic Algorithm Configuration -- 3 Configuration Scenarios -- 4 GCC Configuration Scenarios Analysis -- 5 Experimental Results -- 6 Conclusion and Future Work -- References -- Offline Learning for Selection Hyper-heuristics with Elman Networks -- 1 Introduction -- 2 Methodology -- 2.1 HyFlex and the Offline Learning Database -- 2.2 Final Log Returns and the BEST Sequences -- 2.3 Elman Networks -- 2.4 Training Sets -- 2.5 The BLIND Hyper-heuristic -- 3 Results -- 3.1 Network Training -- 3.2 Evaluating the Elman Network Sequences -- 4 Conclusions -- References -- Author Index. |
| Record Nr. | UNINA-9910349425603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
First Complex Systems Digital Campus world e-conference 2015 [[electronic resource] /] / edited by Paul Bourgine, Pierre Collet, Pierre Parrend
| First Complex Systems Digital Campus world e-conference 2015 [[electronic resource] /] / edited by Paul Bourgine, Pierre Collet, Pierre Parrend |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (VIII, 424 p. 120 illus., 96 illus. in color.) |
| Disciplina | 303.4833 |
| Collana | Springer Proceedings in Complexity |
| Soggetto topico |
Statistical physics
Dynamical systems System theory Computational complexity Data mining Computational intelligence Biophysics Biological physics Complex Systems Complexity Data Mining and Knowledge Discovery Computational Intelligence Biological and Medical Physics, Biophysics |
| ISBN | 3-319-45901-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Welcome to CS-DC’15 -- Reconstructing multi-scale dynamics -- Machine learning methods -- A formal model to compute uncertain continuous data -- Knowledge maps -- Analysis of a Planetary Scale Scientific Collaboration Dataset Reveals Novel Patterns -- Epistemology of integrative and predictive sciences -- Information science and the complexity: are we orientated to a transdisciplinary science? -- Synthesis of ecology, biology and ethnographic data -- Bayesian Causalities, Mappings, and Phylogenies: A Social Science Gateway for Modeling Complexity in Ethnographic, Archaeo-, Eco- and Bio-logical Variables -- Multi-level modeling -- Statistical and dynamical properties of networks -- Community detection as an efficient way to attack real networks -- From particles to complex matter -- Chemical garden -- Assembly of molecular metal oxides from the nano to the macroscale via chemical gardens -- Physics of complex systems -- Viscosity scaling in hydrodynamic instabilities in porous media -- A general approach to the linear stability analysis of miscible viscous fingering in porous media -- From individual to social cognition -- From individual to social cognition: Piaget, Jung and commons -- Ecological approach of sport and sport education -- Ecological Dynamics: a theoretical framework for understanding sport performance, physical education and physical -- Emerging dance movements under ecological constraints in Contact Improvisation dancers with different background -- Emerging collective shared behaviors from individual exploration in football small-sided games -- Adaptability in swimming pattern: how do swimmers adapt propulsive action as a function of speed? -- Backstroke start performance prediction -- Flexible perception-action strategies for follow-the-leader coordination -- Dynamic process of pulmonary data analysis: from the athlete mouth to the coach’s hands -- From processing units to computational ecosystems to the cloud -- A multi-agent system approach to load-balancing and resource allocation for distributed computing -- Integrative science of education -- POEM-COPA Collaborative Open Peer Assessment -- Implications of agent-based computational modeling and simulation for preventive education in children with ADHD -- MOOC as a complex system -- From fields to territories to the planet -- Integrative logistics -- Logistics and Territory; integrative approach -- Process modeling of an international transport chain through the simulation tool SIMPROCESS -- Dynamic emissions reduction from vehicles with technical and behavioral approach -- 4p-factories (e-lab) -- Is the Lean Organisation a complex system? -- An artificial immune ecosystem model for hybrid cloud supervision -- Engineering of territory sustainability -- Spatialisation of Soil Erosion Susceptibility Using USLE Model -- Social patterns in multicultural environments Matrimonial patterns and trans-ethnic entities -- Economics as a complex evolutionist system -- A study of heterogeneity in a stock market simulator based on a model of agents that learn from experience in a market with multiple stocks -- Are innovation systems complex systems? -- From molecules to ecosphere -- Ocean biogeochemical dynamics -- Frontal systems as mechanisms of fish aggregation -- Lagrangian approach to phytoplankton mesoscale biogeography in the Kerguelen region -- Lyapunov exponents and oceanic fronts. . |
| Record Nr. | UNINA-9910156332203321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||