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Learning and Intelligent Optimization

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This book constitutes the thoroughly refereed post-conference proceedings of the 6th International Conference on Learning and Int... Weiterlesen
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This book constitutes the thoroughly refereed post-conference proceedings of the 6th International Conference on Learning and Intelligent Optimization, LION 6, held in Paris, France, in January 2012. The 23 long and 30 short revised papers were carefully reviewed and selected from a total of 99 submissions. The papers focus on the intersections and uncharted territories between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. In addition to the paper contributions the conference also included 3 invited speakers, who presented forefront research results and frontiers, and 3 tutorial talks, which were crucial in bringing together the different components of LION community.


Iterative-Deepening Search with On-Line Tree Size Prediction.- A Learning Optimization Algorithm in Graph Theory: Versatile Search for Extremal Graphs Using a Learning Algorithm.- A Math-Heuristic Dantzig-Wolfe Algorithm for the Capacitated Lot Sizing Problem.- Application of the Nested Rollout Policy Adaptation Algorithm to the Traveling Salesman Problem with Time Windows.- Parallel Algorithm Configuration.- Community Detection in Social and Biological Networks Using Differential Evolution.- A Study on Large Population MOEA Using Adaptive e-Box Dominance and Neighborhood Recombination for Many.- Objective Optimization.- A Non-adaptive Stochastic Local Search Algorithm High-Dimensional Model-Based Optimization Based on Noisy Evaluations of Computer Games.- Pilot, Rollout and Monte Carlo Tree Search Methods for Job Shop Scheduling.- Minimizing Time When Applying Bootstrap to Contingency Tables Analysis of Genome-Wide Data.- Quantifying Homogeneity of Instance Sets for Algorithm Configuration.- Automatically Configuring Algorithms for Scaling Performance.- Upper Confidence Tree-Based Consistent Reactive Planning Application to MineSweeper.- Influence of the Migration Period in Parallel Distributed Gas for Dynamic Optimization.- A Hyper-Heuristic Inspired by Pearl Hunting.- Five Phase and Genetic Hive Hyper-Heuristics for the Cross-Domain Search.- Implicit Model Selection Based on Variable Transformations in Estimation of Distribution.- Improving the Exploration in Upper Confidence Trees.- Parallel GPU Implementation of Iterated Local Search for the Travelling Salesman Problem.- Evaluation of a Family of Reinforcement Learning Cross-Domain Optimization Heuristics.-Effect of SMS-EMOA Parameterizations on Hypervolume Decreases. - Effects of Speciation on Evolution of Neural Networks in Highly Dynamic Environments.- Natural Max-SAT Encoding of Min-SAT. A New Hyperheuristic Algorithm for Cross-Domain Search Problems.- Brain Cine-MRI Sequences Registration Using B-Spline Free-Form Deformations and MLSDO Dynamic Optimization Algorithm.- Global Optimization for Algebraic Geometry.- Clause Sharing in Parallel MaxSAT.- An Intelligent Hyper-Heuristic Framework for CHeSC 2011.


Titel: Learning and Intelligent Optimization
Untertitel: 6th International Conference, LION 6, Paris, France, January 16-20, 2012, Revised Selected Papers
EAN: 9783642344138
Format: E-Book (pdf)
Hersteller: Springer Berlin Heidelberg
Genre: IT & Internet
Veröffentlichung: 01.10.2012
Digitaler Kopierschutz: Wasserzeichen
Dateigrösse: 12.04 MB
Anzahl Seiten: 514

Weitere Bände aus der Buchreihe "Lecture Notes in Computer Science"