Artificial Life and Computational Intelligence Third Australasian Conference, ACALCI 2017, Geelong, VIC, Australia, January 31 - February 2, 2017, Proceedings

• Main Authors: Wagner, Markus, Li, Xiaodong, Hendtlass, Tim
• Format: eBook Book
• Language: English
• Published: Cham Springer Nature 2017; Springer; Springer International Publishing AG
• Edition: 1
• Series: LNCS sublibrary. SL 7, Artificial intelligence
• Subjects: Computational intelligence-Congresses; Special computer methods
• ISBN: 9783319516912; 3319516914; 3319516906; 9783319516905

This book constitutes the refereed proceedings of the Third Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2017, held in Geelong, VIC, Australia, in January/February 2017. The 32 papers presented in this volume were carefully reviewed and selected from 47 submissio...

Table of Contents:

• Intro -- Preface -- Organization -- Contents -- Artificial Life and Computational Intelligence -- Extending the Delaunay Triangulation Based Density Measurement to Many-Objective Optimization -- Abstract -- 1 Introduction -- 2 The Delaunay Triangulation Based Density Measurement -- 3 The NSGA-II-DT Algorithm and Its Variations -- 4 Experimental Studies -- 5 Conclusions -- References -- Emotion, Trustworthiness and Altruistic Punishment in a Tragedy of the Commons Social Dilemma -- 1 Introduction -- 2 Background -- 3 System Description -- 4 Results -- 5 Conclusion -- References -- Equity Option Strategy Discovery and Optimization Using a Memetic Algorithm -- 1 Introduction -- 2 Equity Option Overview -- 3 Memetic Algorithm Based Search -- 4 Evolutionary Algorithm Search Results -- 4.1 Maximizing Profit for a 80% Profitable Strategy -- 4.2 Maximizing Profit for a 80% Profitable Strategy While Limiting the Maximum Equity Drawdown to Less Than 10% -- 5 Conclusions -- References -- Co-Evolving Line Drawings with Hierarchical Evolution -- 1 Introduction -- 2 Methodology -- 3 Experiments -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Reliability Estimation of Individual Multi-target Regression Predictions -- 1 Introduction -- 2 Related Work -- 2.1 Multi-target Modeling -- 2.2 Reliability Estimation of Single-Target Predictions -- 3 Reliability Estimation of Multi-target Predictions -- 3.1 Independent Estimation for Each Target Variable -- 3.2 Aggregation of Independent Reliability Estimates -- 3.3 Generalization to Multi-target Prediction -- 4 Evaluation and Results -- 4.1 Performance with Different Predictive Models -- 4.2 Correlations with the Prediction Error -- 5 Conclusion -- References -- Feedback Modulated Attention Within a Predictive Framework -- 1 Introduction -- 2 Related Work -- 3 Temporal Pooler Plus Attention
• 4.2 Further Analyses -- 5 Conclusions and Future Work -- References -- Surrogate-Assisted Multi-swarm Particle Swarm Optimization of Morphing Airfoils -- 1 Introduction -- 2 Geometrical Parametrization -- 3 Surrogate Model -- 3.1 Kriging Method -- 4 Particle Swarm Optimization -- 4.1 Optimization in a Dynamic Environment -- 5 Implementation of the Surrogate Model -- 6 Application -- 7 Results -- 8 Conclusion -- References -- Applying Dependency Patterns in Causal Discovery of Latent Variable Models -- 1 Introduction -- 1.1 Causal Bayesian Networks -- 1.2 Latent Variable Discovery -- 2 Triggers in Latent Variable Discovery -- 3 Generating Simulated Datasets of Triggers -- 4 Learning Triggers by FCI and PC Algorithms -- 5 Causal MML (CaMML) -- 6 Applying Triggers in CaMML -- 7 Conclusion -- References -- An Evolutionary Multi-criteria Journey Planning Algorithm for Multimodal Transportation Networks -- 1 Introduction -- 2 Preliminaries -- 3 Prior Work -- 4 Problem Formulation -- 4.1 Input Network -- 4.2 Weight Assignment Strategies -- 5 Proposed Method -- 5.1 Personalized Multi-criteria Genetic Algorithm (PMGA) -- 5.2 Basic Operators of the Proposed Algorithm -- 6 Experiment -- 6.1 Quality Indicators -- 6.2 Experimentation Results and Discussion -- 7 Conclusion -- References -- Estimating Passenger Preferences Using Implicit Relevance Feedback for Personalized Journey Planning -- 1 Introduction -- 2 Prior Work -- 3 Problem Formulation -- 3.1 Input Network -- 3.2 Personalized Multi-criteria Journey Planning Paradigm (MCJP) -- 4 Proposed Preference Learning Method -- 4.1 Preferences Estimating -- 4.2 An Illustrative Example of Our Approach -- 5 Experiment -- 6 Conclusion -- References -- Quantitative Assessment of Heart Function: A Hybrid Mechanism for Left Ventricle Segmentation from Cine MRI Sequences -- Abstract -- 1 Introduction
• 2.2 An Illustrative Example for DOPUAV -- 3 Detectable Genetic Algorithms-Based Techniques -- 3.1 Change Detection Process -- 3.2 Mask Detection Process -- 4 Experimental Setup and Results -- 4.1 DetGA Variations -- 4.2 Comparing with State-of-the-Art Algorithms -- 5 Summary and Future Work -- References -- Neighbourhood Analysis: A Case Study on Google Machine Reassignment Problem -- 1 Introduction -- 2 Problem Description -- 3 Methodology -- 4 Experiments -- 5 Results -- 6 Discussion -- 7 Conclusions -- 8 Future Work -- References -- Optimisation Algorithms and Applications -- Multi-objective Optimisation with Multiple Preferred Regions -- 1 Introduction -- 2 Definitions and Basic Principles -- 3 Preferred Regions for Different MOEAs -- 3.1 Ideas Adopted in pNSGAII -- 3.2 pAGE -- 4 Experimental Study -- 4.1 Experimental Setup -- 4.2 Results and Discussion -- 5 pNSGAII on Energy System Optimization Problem -- 6 Conclusions -- References -- An Adaptive Memetic Algorithm for the Architecture Optimisation Problem -- 1 Introduction -- 2 Related Work -- 3 Component Deployment -- 3.1 Reliability Estimation -- 4 Adaptive Memetic Algorithm -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Problem Instances -- 5.3 Benchmark Optimisation Algorithms -- 6 Results -- 7 Conclusion -- References -- Resource Constrained Job Scheduling with Parallel Constraint-Based ACO -- 1 Introduction -- 2 Problem Specification -- 3 CP-Beam-ACO -- 4 Parallel CP-Beam-ACO -- 4.1 Parallelized Stochastic Sampling -- 4.2 Full Parallelization -- 5 Experiments and Results -- 5.1 Comparing Speedup -- 5.2 Comparing Feasibility -- 5.3 Comparing Solution Quality -- 6 Discussion -- 7 Conclusion -- References -- An Iterated Local Search with Guided Perturbation for the Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Three-Dimensional Loading Constraints -- 1 Introduction
• 3.1 Predicting Temporal Sequences -- 3.2 Outputting the Prediction Error -- 3.3 Attentional Filtering -- 3.4 Learning -- 4 Experiments and Analysis -- 4.1 Burst Sequences -- 4.2 Frequent Feature Sequences -- 5 Discussion -- 6 Conclusion -- References -- A Batch Infill Strategy for Computationally Expensive Optimization Problems -- 1 Introduction and Background -- 2 Proposed Approach -- 2.1 Initialization -- 2.2 Archive Update -- 2.3 Constructing/Updating Kriging Models -- 2.4 Identifying Infill Samples -- 2.5 Updating Best Solution -- 3 Numerical Experiments -- 3.1 Experimental Settings -- 3.2 Performance Metrics -- 3.3 Experimental Results -- 4 Summary and Future Work -- References -- Automatic Clustering and Summarisation of Microblogs: A Multi-subtopic Phrase Reinforcement Algorithm -- 1 Introduction -- 2 Related Work -- 3 Multi-subtopic Summarisation of Microblogging Posts -- 3.1 The Original PR Algorithm -- 3.2 The K-means Clustering Algorithm -- 3.3 The PRICE Algorithm -- 4 Experimental Evaluation -- 4.1 Data Collection and Pre-processing -- 4.2 Automatic and Manual Summarisation -- 4.3 Evaluation Metrics -- 4.4 Results -- 5 Conclusions and Future Work -- References -- Generation and Exploration of Architectural Form Using a Composite Cellular Automata -- 1 Introduction -- 2 Background -- 2.1 Computational Morphogenesis -- 2.2 Cellular Automata -- 2.3 Cellular Automata and Design -- 3 Model -- 4 Experiments -- 4.1 Methodology -- 4.2 Results -- 5 Discussion and Conclusion -- References -- Wrapper Feature Construction for Figure-Ground Image Segmentation Using Genetic Programming -- 1 Introduction -- 1.1 Goal -- 2 The Proposed Methods -- 2.1 CoevoGPMFC -- 2.2 WrapperGPSFC -- 3 Experiment Preparations -- 3.1 GP Settings -- 3.2 Datasets -- 3.3 Evaluation Measures -- 3.4 Experiment Design -- 4 Results -- 4.1 Training and Test Performance
• 2 Literature Review -- 2.1 Histogram-Based Methods -- 2.2 Statistical Model-Based Methods -- 2.3 Region-Based Methods -- 2.4 Graph-Based Methods -- 2.5 Deformable Model-Based Methods -- 2.6 Atlas-Based Methods -- 3 Methodology -- 4 Experimental Results -- 5 Conclusion and Future Work -- Acknowledgments -- References -- A Hybrid Feature Selection Scheme Based on Local Compactness and Global Separability for Improving Roller Bearing Diagnostic Performance -- Abstract -- 1 Introduction -- 2 Experiment Setup and Acoustic Emission Signal Acquisition -- 3 Proposed Fault Diagnosis Methodology -- 3.1 Heterogeneous Feature Extraction Models -- 3.2 Proposed HFS-LCGS Scheme -- 3.3 Fault Classification for Online Diagnosis -- 4 Experiment Results and Discussion -- 5 Conclusions -- Acknowledgments -- References -- Reliable Fault Diagnosis of Bearings Using Distance and Density Similarity on an Enhanced k-NN -- Abstract -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Data Acquisition -- 2.2 Feature Extraction -- 2.3 Assign Membership Values to the Test Sample -- 2.3.1 Probability of Class Information Based on the Distance ( \alpha ) -- 2.3.2 Probability of Class Information Based on the Density ( \beta ) -- 2.3.3 Assigning Membership Values -- 2.4 Classification -- 3 Experimental Results and Analysis -- 4 Conclusions -- Acknowledgements -- References -- Towards Solving TSPN with Arbitrary Neighborhoods: A Hybrid Solution -- Abstract -- 1 Introduction -- 2 Methodology -- 3 Framework -- 4 Experiments -- 4.1 Case Studies -- 4.2 Problem Analysis -- 5 Conclusion -- Acknowledgement -- References -- Detectable Genetic Algorithms-Based Techniques for Solving Dynamic Optimisation Problem with Unknown Active Variables -- Abstract -- 1 Introduction -- 2 Dynamic Optimisation Problem with Unknown Active Variables -- 2.1 Mask Creation
• 2 Related Work