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• Introduction
• Reconfigurable Hardware
• Evolutionary Algorithms
• Evolvable Hardware
• Towards Evolvable Components
• Evolvable Computational Machines
• An Evolvable Component for Image-Pre-processing
• Virtual Reconfigurable Devices
• Concluding Statements
• References
• Index.
• (source: Nielsen Book Data)

This book deals with adaptive evolvable systems operating in a changing environment. The proposed component approach for the design of evolvable systems, the mathematical theory of evolvable machines, and the idea of virtual reconfigurable circuits have opened a way towards a better understanding of evolvable systems and to the design of more adaptive, competitive and innovative engineering products. In particular, topics such as the computational power of evolvable systems, the design of complex human-competitive digital circuits and the implementation of a one-clock partial reconfiguration in a common field-programmable gate array are introduced, investigated and implemented. The application domain is adaptive image preprocessing.
(source: Nielsen Book Data)

• Evolution of Analog Circuits
• Unconstrained Evolution of Analogue Computational "QR" Circuit with Oscillating Length Representation
• ISCLEs: Importance Sampled Circuit Learning Ensembles for Trustworthy Analog Circuit Topology Synthesis
• Evolution of Digital Circuits
• A Comparison of Evolvable Hardware Architectures for Classification Tasks
• Hardware Acceleration of an Immune Network Inspired Evolutionary Algorithm for Medical Diagnosis
• A Stepwise Dimension Reduction Approach to Evolutionary Design of Relative Large Combinational Logic Circuits
• Hardware-Software Codesign and Platforms for Adaptive Systems
• Evolutionary Graph Models with Dynamic Topologies on the Ubichip
• A Hardware-Software Design Framework for Distributed Cellular Computing
• Hardware/Software Co-synthesis of Distributed Embedded Systems Using Genetic Programming
• Self-Adaptive Networked Entities for Building Pervasive Computing Architectures
• Best Paper Award Competition
• Cellular Automata-Based Development of Combinational and Polymorphic Circuits: A Comparative Study
• Investigating the Suitability of FPAAs for Evolved Hardware Spiking Neural Networks
• The Segmental-Transmission-Line: Its Design and Prototype Evaluation
• On Evolutionary Synthesis of Linear Transforms in FPGA
• Evolutionary Robotics
• Towards Efficient Evolutionary Design of Autonomous Robots
• Indirect Online Evolution
• A Conceptual Framework for Adaptation in Industrial Robotic Systems
• Development
• A Developmental Gene Regulation Network for Constructing Electronic Circuits
• Discovery and Investigation of Inherent Scalability in Developmental Genomes
• Learning General Solutions through Multiple Evaluations during Development
• Real-World Applications
• Evolving MEMS Resonator Designs for Fabrication
• Self-Reconfigurable Mixed-Signal Integrated Circuits Architecture Comprising a Field Programmable Analog Array and a General Purpose Genetic Algorithm IP Core
• Evolutionary Networking
• Proposal for LDPC Code Design System Using Multi-Objective Optimization and FPGA-Based Emulation
• Scalability of a Novel Shifting Balance Theory-Based Optimization Algorithm: A Comparative Study on a Cluster-Based Wireless Sensor Network
• Evolutionary Design of Fault Tolerant Collective Communications
• Evolvable Artificial Neural Networks
• A Cellular Structure for Online Routing of Digital Spiking Neuron Axons and Dendrites on FPGAs
• Bio-inspired Event Coded Configurable Analog Circuit Block
• Dynamics of Firing Patterns in Evolvable Hierarchically Organized Neural Networks
• Transistor-Level Circuit Evolution
• Evolving Variability-Tolerant CMOS Designs
• Transistor-Level Evolution of Digital Circuits Using a Special Circuit Simulator
• Extended Posters
• Optimised State Assignment for FSMs Using Quantum Inspired Evolutionary Algorithm
• Evolvable Hardware: A Tool for Reverse Engineering of Biological Systems
• Coevolution of Neuro-developmental Programs That Play Checkers
• Hippocampus-Inspired Spiking Neural Network on FPGA
• Fault-Tolerant Memory Design and Partitioning Issues in Embryonics
• The Input Pattern Order Problem: Evolution of Combinatorial and Sequential Circuits in Hardware
• Neural Development on the Ubichip by Means of Dynamic Routing Mechanisms
• Short Posters
• The Perplexus Programming Framework: Combining Bio-inspiration and Agent-Oriented Programming for the Simulation of Large Scale Complex Systems
• Quantum Bio-inspired Vision Model on System-on-a-Chip (SoC)
• Evolutionary Meta Compilation: Evolving Programs Using Real World Engineering Tools
• Waveguide Synthesis by Genetic Algorithms with Multiple Crossover
• Parallel Grammatical Evolution for Circuit Optimization
• Self-organization of Bio-inspired Integrated Circuits
• Artificial Creativity in Linguistics Using Evolvable Fuzzy Neural Networks.

This book constitutes the refereed proceedings of the 8th International Conference on Evolvable Systems, ICES 2008, held in Prague, Czech Republic, in September 2008. The 28 revised full papers and 14 revised poster papers presented were carefully reviewed and selected from 52 submissions. The papers are organized in topical sections on evolution of analog circuits, evolution of digital circuits, hardware-software codesign and platforms for adaptive systems, evolutionary robotics, development, real-world applications, evolutionary networking, evolvable artificial neural networks, and transistor-level circuit evolution.
(source: Nielsen Book Data)

• [I]. Long presentations: 1. Ariadne : evolving test data using grammatical evolution / Muhammad Sheraz Anjum, Conor Ryan
• 2. Quantum program synthesis : swarm algorithms and benchmarks / Timothy Atkinson, Athena Karsa, John Drake, Jerry Swan
• 3. A genetic programming approach to predict mosquitoes abundance / Riccardo Gervasi, Irene Azzali, Donal Bisanzio, Andrea Mosca, Luigi Bertolotti, Mario Giacobini
• 4. Complex network analysis of a genetic programming phenotype network / Ting Hu, Marco Tomassini, Wolfgang Banzhof
• 5. Improving genetic programming with novel exploration : exploitation control / Jonathan Kelly, Erik Hemberg, Una-May O'Reilly
• 6. Towards a scalable EA-based optimization of digital circuits / Jitka Kocnova, Zdenek Vasicek
• 7. Cartesian genetic programming as an optimizer of programs evolved with geometric semantic genetic programming / Ondrej Koncal, Lukas Sekanina
• 8. Can genetic programming do manifold learning too? / Andrew Lensen, Bing Xue, Mengjie Zhang
• 9. Why is auto-encoding difficult for genetic programming? / James McDermott
• 10. Solution and fitness evolution (SAFE) : coevolving solutions and their objective functions / Moshe Sipper, James H. Moore, Ryan J. Urbanowicz
• 11. A model of external memory for navigation in partially observable visual reinforcement learning tasks / Robert J. Smith, Malcolm I. Heywood
• 12. Fault detection and classification for induction motors using genetic programming / Yu Zhang, Ting Hu, Xiaodong Liang, Mohammad Zawad Ali, Md. Nasmus Sakib Khan Shabbir.

• [II]. Short presentations: 13. Fast DENSER : efficient deep NeuroEvolution / Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro
• 14. A vectorial approach to genetic programming / Irene Azzali, Leonardo Vanneschi, Sara Silva, Illya Bakurov, Mario Giacobini
• 15. Comparison of genetic programming methods on design of cryptographic Boolean functions / Jakub Husa
• 16. Evolving AVX512 parallel C code using GP / William B. Langdon, Ronny Lorenz
• 17. Hyper-bent Boolean functions and evolutionary algorithms / Luca Mariot, Domagoj Jakobovic, Alberto Leporati, Stjepan Picek
• 18. Learning class disjointness axioms using grammatical evolution / Thu Huong Nguyen, Andrea G.B. Tettamanzi.

This book constitutes the refereed proceedings of the 22nd European Conference on Genetic Programming, EuroGP 2019, held as part of Evo* 2019, in Leipzig, Germany, in April 2019, co-located with the Evo* events EvoCOP, EvoMUSART, and EvoApplications. The 12 revised full papers and 6 short papers presented in this volume were carefully reviewed and selected from 36 submissions. They cover a wide range of topics and reflect the current state of research in the field. With a special focus on real-world applications in 2019, the papers are devoted to topics such as the test data design in software engineering, fault detection and classification of induction motors, digital circuit design, mosquito abundance prediction, machine learning and cryptographic function design. .
(source: Nielsen Book Data)

• Using GP Is NEAT: Evolving Compositional Pattern Production Functions.- Evolving the Topology of Large Scale Deep Neural Networks.- Evolving Graphs by Graph Programming.- Pruning Techniques for Mixed Ensembles of Genetic Programming Models.- Analyzing Feature Importance for Metabolomics Using Genetic Programming.- Generating Redundant Features with Unsupervised Multi-Tree Genetic Programming.- On the Automatic Design of a Representation for Grammar-Based Genetic Programming.- Multi-Level Grammar Genetic Programming for Scheduling in Heterogeneous Networks.- Scaling Tangled Program Graphs to Visual Reinforcement Learning in ViZDoom.- Towards In Vivo Genetic Programming: Evolving Boolean Networks to Determine Cell States.- A Multiple Expression Alignment Framework for Genetic Programming.- Multi-Objective Evolution of Ultra-Fast General-Purpose Hash Functions.- A Comparative Study on Crossover in Cartesian Genetic Programming.- Evolving Better RNAfold Structure Prediction.- Geometric Crossover in Syntactic Space.- Investigating A Machine Breakdown Genetic Programming Approach for Dynamic Job Shop Scheduling.- Structurally Layered Representation Learning: Towards Deep Learning Through Genetic Programming.- Comparing Rule Evaluation Metrics for the Evolutionary Discovery of Multi-Relational Association Rules in the Semantic Web.- Genetic Programming Hyperheuristic with Cooperative Coevolution for Dynamic Flexible Job Shop Scheduling. .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 21st European Conference on Genetic Programming, EuroGP 2018, held in Parma, Italy, in April 2018, co-located with the Evo* 2018 events, EvoCOP, EvoMUSART, and EvoApplications. The 11 revised full papers presented together with 8 poster papers were carefully reviewed and selected from 36 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics and applications including analysis of feature importance for metabolomics, semantic methods, evolution of boolean networks, generation of redundant features, ensembles of GP models, automatic design of grammatical representations, GP and neuroevolution, visual reinforcement learning, evolution of deep neural networks, evolution of graphs, and scheduling in heterogeneous networks.
(source: Nielsen Book Data)

• Intro; Preface; Organization; Contents; Oral Presentations; Evolutionary Program Sketching; 1 Introduction; 2 Program Sketching; 3 Evolutionary Program Sketching; 3.1 Problem Specification; 3.2 Instruction Set; 3.3 Fitness Function; 3.4 Exploiting the Feedback from Hole Completion; 4 Related Work; 5 Experimental Evaluation; 6 Discussion; 7 Conclusion; References; Exploring Fitness and Edit Distance of Mutated Python Programs; 1 Introduction; 2 Related Work; 3 Our Implementation of Genetic Improvement; 3.1 Fitness Function; 3.2 Search Algorithm; 4 Experimental Setup

• 4.1 Description of the Programs Targeted by GI5 Results; 5.1 Change in Fitness; 5.2 Average Fitness with Respect to Edit List Size; 5.3 Discrete Steps in Fitness; 6 Conclusions; References; Differentiable Genetic Programming; 1 Introduction; 2 Program Encoding; 3 The Algebra of Truncated Polynomials; 3.1 The Link to Taylor Polynomials; 3.2 Non Rational Functions; 4 Example of a dCGP; 5 Learning Constants in Symbolic Regression; 5.1 Ephemeral Constants Approach; 5.2 Weighted dCGP Approach; 6 Solution to Differential Equations; 7 Discovery of Prime Integrals; 8 Conclusions; References

• Evolving Game State Features from Raw Pixels1 Introduction; 2 Related Research; 3 Materials; 3.1 Games; 3.2 Handcrafted Game State Features; 4 Evolving Video Game State Visual Features Using Genetic Programming; 4.1 Evolving Game State Features; 4.2 Voting for Actions; 5 Results; 6 Conclusion; References; Emergent Tangled Graph Representations for Atari Game Playing Agents; 1 Introduction; 2 Background; 3 The Arcade Learning Environment; 3.1 Screen State Space Representation; 4 Evolving Tangled Program Graphs; 4.1 Coevolving Teams of Programs; 4.2 Emergent Modularity

• 4.3 Diversity Maintenance5 Empirical Experiments; 5.1 Experimental Setup; 5.2 Results; 5.3 Solution Analysis; 6 Conclusion and Future Work; References; A General Feature Engineering Wrapper for Machine Learning Using -Lexicase Survival; 1 Introduction; 2 Feature Engineering Wrapper; 2.1 -lexicase Survival; 2.2 Scaling; 3 Related Work; 4 Experimental Analysis; 4.1 Problems; 5 Results; 5.1 Hyper-Parameter Optimization; 5.2 Problem Performance; 5.3 Statistical Analysis; 6 Discussion; 7 Conclusions; References; Visualising the Search Landscape of the Triangle Program; 1 Genetic Improvement

• 2 Triangle Program Software Engineering Benchmark3 Binary Representation: Replacing Comparisons with One Alternative; 3.1 High Order Binary Schema Are Not Deceptive; 3.2 Binary Schema Predict All Solutions of the Triangle Program; 3.3 Local Search Landscape of the Binary Space; 4 Original All Comparisons; 4.1 Fitness Space of Triangle Program; 4.2 High Order Schema Analysis; 4.3 Local Search for the Triangle Program; 4.4 Local Optima Networks; 5 Conclusions; References; RANSAC-GP: Dealing with Outliers in Symbolic Regression with Genetic Programming; 1 Introduction; 2 Background; 2.1 Outliers

This book constitutes the refereed proceedings of the 20th European Conference on Genetic Programming, EuroGP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo* 2017 events, EvoCOP, EvoMUSART, and EvoApplications. The 14 revised full papers presented together with 8 poster papers were carefully reviewed and selected from 32 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics and applications including program synthesis, genetic improvement, grammatical representations, self-adaptation, multi-objective optimisation, program semantics, search landscapes, mathematical programming, games, operations research, networks, evolvable hardware, and program synthesis benchmarks.
(source: Nielsen Book Data)