Parallel Problem Solving from Nature – PPSN XV

Table of Contents

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   Book Overview
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   Chapter 1 A General Dichotomy of Evolutionary Algorithms on Monotone Functions
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   Chapter 2 Artificial Immune Systems Can Find Arbitrarily Good Approximations for the NP-Hard Partition Problem
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   Chapter 3 A Simple Proof for the Usefulness of Crossover in Black-Box Optimization
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   Chapter 4 Destructiveness of Lexicographic Parsimony Pressure and Alleviation by a Concatenation Crossover in Genetic Programming
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   Chapter 5 Exploration and Exploitation Without Mutation: Solving the Jump Function in $$\varTheta (n)$$ Time
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   Chapter 6 Fast Artificial Immune Systems
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   Chapter 7 First-Hitting Times for Finite State Spaces
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   Chapter 8 First-Hitting Times Under Additive Drift
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    Chapter 9 Level-Based Analysis of the Population-Based Incremental Learning Algorithm
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    Chapter 10 Precise Runtime Analysis for Plateaus
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    Chapter 11 Ring Migration Topology Helps Bypassing Local Optima
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    Chapter 12 Runtime Analysis of Evolutionary Algorithms for the Knapsack Problem with Favorably Correlated Weights
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    Chapter 13 Theoretical Analysis of Lexicase Selection in Multi-objective Optimization
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    Chapter 14 Towards a Running Time Analysis of the (1+1)-EA for OneMax and LeadingOnes Under General Bit-Wise Noise
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    Chapter 15 A Surrogate Model Based on Walsh Decomposition for Pseudo-Boolean Functions
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    Chapter 16 Bridging Elementary Landscapes and a Geometric Theory of Evolutionary Algorithms: First Steps
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    Chapter 17 Empirical Analysis of Diversity-Preserving Mechanisms on Example Landscapes for Multimodal Optimisation
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    Chapter 18 Linear Combination of Distance Measures for Surrogate Models in Genetic Programming
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    Chapter 19 On Pareto Local Optimal Solutions Networks
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    Chapter 20 Perturbation Strength and the Global Structure of QAP Fitness Landscapes
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    Chapter 21 Sampling Local Optima Networks of Large Combinatorial Search Spaces: The QAP Case
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    Chapter 22 Algorithm Configuration Landscapes:
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    Chapter 23 A Model-Based Framework for Black-Box Problem Comparison Using Gaussian Processes
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    Chapter 24 A Suite of Computationally Expensive Shape Optimisation Problems Using Computational Fluid Dynamics
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    Chapter 25 Automated Selection and Configuration of Multi-Label Classification Algorithms with Grammar-Based Genetic Programming
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    Chapter 26 Performance Assessment of Recursive Probability Matching for Adaptive Operator Selection in Differential Evolution
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    Chapter 27 Program Trace Optimization
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    Chapter 28 Sampling Heuristics for Multi-objective Dynamic Job Shop Scheduling Using Island Based Parallel Genetic Programming
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    Chapter 29 Sensitivity of Parameter Control Mechanisms with Respect to Their Initialization
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    Chapter 30 Tailoring Instances of the 1D Bin Packing Problem for Assessing Strengths and Weaknesses of Its Solvers
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    Chapter 31 Adaptive Advantage of Learning Strategies: A Study Through Dynamic Landscape
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    Chapter 32 A First Analysis of Kernels for Kriging-Based Optimization in Hierarchical Search Spaces
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    Chapter 33 Challenges in High-Dimensional Reinforcement Learning with Evolution Strategies
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    Chapter 34 Lamarckian Evolution of Convolutional Neural Networks
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    Chapter 35 Learning Bayesian Networks with Algebraic Differential Evolution
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    Chapter 36 Optimal Neuron Selection and Generalization: NK Ensemble Neural Networks
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    Chapter 37 What Are the Limits of Evolutionary Induction of Decision Trees?
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    Chapter 38 Tutorials at PPSN 2018
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    Chapter 39 Workshops at PPSN 2018