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• A Study of Energy Reduction Strategies in Renewable Hybrid Grid.- Classification and Watermarking of Brain Tumor using Artificial and Convolutional Neural Networks.- A Proposal for a Deep Learning Model to Enhance Student Guidance and Reduce Dropout.- EduBot: An Unsupervised Domain-Specific Chatbot for Educational Institutions.- SQL Generation from Natural Language using Supervised Learning and Recurrent Neural Networks.- Toward Intelligent Solution to Identify Learner Attitude from Source Code.
• (source: Nielsen Book Data)

This book gathers selected papers from Artificial Intelligence and Industrial Applications (A2IA'2020), the first installment of an annual international conference organized by ENSAM-Meknes at Moulay Ismail University, Morocco. The 29 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as digital twin, multiagent systems, deep learning, image processing and analysis, control, prediction, modeling, optimization and design, as well as AI applications in industry, health, energy, agriculture, and education. The book is intended for AI experts, offering them a valuable overview and global outlook for the future, and highlights a wealth of innovative ideas and recent, important advances in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.
(source: Nielsen Book Data)

• Minimum Diameter $k$-Steiner Forest.- Factors Impacting the Label Denoising of Neural Relation Extraction.- Makespan Minimization on Unrelated Parallel Machines with a Few Bags.- Channel Assignment with r-Dynamic Coloring.- Profit Maximization Problem with Coupons in Social Networks.- A Bicriteria Approximation Algorithm for Minimum Submodular Cost Partial Multi-Cover Problem.- A Novel Approach to Verifying Context Free Properties of Programs.- Determination of Dual Distances for a Kind of Perfect Mixed Codes.- Approximation and Competitive Algorithms for Single-Minded Selling Problem.- An Empirical Analysis of Feasibility Checking Algorithms for UTVPI Constraints.- Quality-aware Online Task Assignment Using Latent Topic Model.- Calibration Scheduling with Time Slot Cost.- The k-power domination problem in weighted trees.- General Rumor Blocking: An Efficient Random Algorithm with Martingale Approach.- A Robust Power Optimization Algorithm to Balance Base Stations' Load in LTE-A Network.- Faster Compression of Patterns to Rectangle Rule Lists.- Algorithm Designs for Dynamic Ridesharing System.- New LP Relaxations for Minimum Cycle/Path/Tree Cover Problems.- Computation of Kullback-Leibler Divergence between Labeled Stochastic Systems with Non-Identical State Spaces.- Order preserving barrier coverage with weighted sensors on a line.- Achieving Location Truthfulness in Rebalancing Supply-Demand Distribution for Bike Sharing.- Approximation algorithms and a hardness result for the three-machine proportionate mixed-shop problem.- A New Algorithm Design Technique for Hard Problems, Building on Methods of Complexity Theory.- Community-based Acceptance Probability Maximization for Target Users on Social Networks.- Knowledge Graph Embedding Based on Subgraph-aware Proximity.
• (source: Nielsen Book Data)

This volume constitutes the proceedings of the 12th International Conference on Algorithmic Aspects in Information and Management, AAIM 2018, held in Dallas, Texas, USA, in December 2018. The 25 full papers presented were carefully reviewed and selected. The papers deal with current trends of research on algorithms, data structures, operation research, combinatorial optimization and their applications.
(source: Nielsen Book Data)

• Intro; Preface; Organization; Contents; Time Series Representation and Compression; Symbolic Representation of Time Series: A Hierarchical Coclustering Formalization; 1 Introduction; 2 Related Work; 3 Formalization of the SAXO Approach; 3.1 Prior Distribution of the SAXO Models; 3.2 Likelihood of Data Given a SAXO Model; 3.3 Evaluation Criterion; 4 Comparative Experiments on Real Datasets; 4.1 Coding Length Evaluation; 4.2 Supervised Learning Evaluation; 5 Conclusion and Perspectives; References; Dense Bag-of-Temporal-SIFT-Words for Time Series Classification; 1 Introduction; 2 Related Work

• 2.1 Distance-Based Time Series Classification2.2 Bag-of-Words for Time Series Classification; 2.3 Ensemble Classifiers for Time Series; 3 Bag-of-Temporal-SIFT-Words (BoTSW); 3.1 Keypoint Extraction in Time Series; 3.2 Description of the Extracted Keypoints; 3.3 Bag-of-Temporal-SIFT-Words for Time Series Classification; 4 Experiments and Results; 4.1 Experimental Setup; 4.2 Dense Extraction vs. Scale-Space Extrema Detection; 4.3 Impact of the BoW Normalization; 4.4 Comparison with State-of-the-Art Methods; 5 Conclusion; References

• Dimension Reduction in Dissimilarity Spaces for Time Series Classification1 Introduction; 2 Related Work; 3 Dissimilarity Representations of Time Series; 3.1 The Basic Idea; 3.2 Dynamic Time Warping Distance; 3.3 Dissimilarity Representations; 3.4 Learning Classifiers in Dissimilarity Space; 3.5 Prototype Dependent Kernels; 4 Experiments; 4.1 Data; 4.2 Classifiers; 4.3 Experimental Protocol; 4.4 Results; 5 Conclusion; A Performance Profiles; References; Time Series Classification and Clustering; Fuzzy Clustering of Series Using Quantile Autocovariances; 1 Introduction

• 2 A Dissimilarity Based on Quantile Autocovariances3 Fuzzy Clustering Based on Quantile Autocovariances; 4 Simulation Study; 5 A Case Study; 6 Concluding Remarks; References; A Reservoir Computing Approach for Balance Assessment; 1 Introduction; 2 Balance Assessment Using Reservoir Computing; 3 Experimental Results; 4 Conclusions; References; Learning Structures in Earth Observation Data with Gaussian Processes; 1 Introduction; 2 Gaussian Process Regression; 2.1 Gaussian Processes: A Gentle Introduction; 2.2 On the Model Selection; 2.3 On the Covariance Function

• 2.4 Gaussian Processes Exemplified3 Advances in Gaussian Process Regression; 3.1 Structured, Non-stationary and Multiscale; 3.2 Time-based Covariance for GPR; 3.3 Heteroscedastic GPR: Learning the Noise Model; 3.4 Warped GPR: Learning the Output Transformation; 3.5 Source Code and Toolboxes; 4 Analysis of Gaussian Process Models; 4.1 Ranking Features Through the ARD Covariance; 4.2 Uncertainty Intervals; 5 Conclusions and Further Work; References; Monitoring Short Term Changes of Infectious Diseases in Uganda with Gaussian Processes; 1 Introduction; 2 Methods Used

This book constitutes the refereed proceedings of the First ECML PKDD Workshop, AALTD 2015, held in Porto, Portugal, in September 2016. The 11 full papers presented were carefully reviewed and selected from 22 submissions. The first part focuses on learning new representations and embeddings for time series classification, clustering or for dimensionality reduction. The second part presents approaches on classification and clustering with challenging applications on medicine or earth observation data. These works show different ways to consider temporal dependency in clustering or classification processes. The last part of the book is dedicated to metric learning and time series comparison, it addresses the problem of speeding-up the dynamic time warping or dealing with multi-modal and multi-scale metric learning for time series classification and clustering.

• Robust Functional Regression for Outlier Detection
• Transform Learning Based Function Approximation for Regression and Forecasting
• Proactive Fiber Break Detection based on Quaternion Time Series and Automatic Variable Selection from Relational Data
• A fully automated periodicity detection in time series
• Conditional Forecasting of Water Level Time Series with RNNs
• Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories
• Localized Random Shapelets
• Feature-Based Gait Pattern Classification for a Robotic Walking Frame
• How to detect novelty in textual data streams? A comparative study of existing methods
• Seq2VAR: multivariate time series representation with relational neural networks and linear autoregressive model
• Modelling Patient Sequences for Rare Disease Detection with Semi-supervised Generative Adversarial Nets
• Extended Kalman Filter for Large Scale Vessels Trajectory Tracking in Distributed Stream Processing Systems
• Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets using Deep Learning
• Learning Stochastic Dynamical Systems via Bridge Sampling
• Quantifying Quality of Actions Using Wearable Sensor
• An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis.

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Würzburg, Germany, in September 2019. The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover topics such as temporal data clustering; classification of univariate and multivariate time series; early classification of temporal data; deep learning and learning representations for temporal data; modeling temporal dependencies; advanced forecasting and prediction models; space-temporal statistical analysis; functional data analysis methods; temporal data streams; interpretable time-series analysis methods; dimensionality reduction, sparsity, algorithmic complexity and big data challenge; and bio-informatics, medical, energy consumption, on temporal data.

• Intro; Preface; Organization; Contents; On the Trustworthy Fulfillment of Commitments; 1 Motivation; 2 Computational Models of Commitment; 3 Problem Formulation; 4 Commitment Semantics; 4.1 Relationship to Other Commitment Semantics; 4.2 Semantics-Respecting Algorithms; 4.3 Semantics with Other Kinds of Uncertainty; 5 Implications for Non-Decision-Theoretic Agents; 6 Conclusions; References; Evaluating the Efficiency of Robust Team Formation Algorithms; 1 Introduction; 2 Problem Definition; 3 Related Work; 4 Approximations of the TORTF Problem; 4.1 Greedy Algorithms; 4.2 Genetic Algorithm

• 4.3 Linear Programming Approach5 Results and Discussion; 5.1 Datasets; 5.2 Results; 6 Conclusions; References; Social Welfare in One-Sided Matching Mechanisms; 1 Introduction; 1.1 Our Results; 1.2 Discussion and Related Work; 2 Preliminaries; 3 Price of Anarchy Guarantees; 4 Lower Bounds; 5 General Solution Concepts; 6 Extensions; 6.1 Price of Stability; 6.2 Unit-Range Representation; 7 Conclusion and Future Work; References; Using Multiagent Negotiation to Model Water Resources Systems Operations; 1 Introduction; 2 Related Work; 3 The Case Study; 4 The Negotiation Protocols

• 4.1 Point-Based Protocol4.2 Set-Based Protocol; 5 Simulations; 6 Conclusions; References; To Big Wing, or Not to Big Wing, Now an Answer; 1 Introduction; 1.1 The Battle of Britain; 1.2 The Lanchester Model; 1.3 Agent Based Models; 2 Model Design; 2.1 RAF Forces; 2.2 German Forces; 2.3 Model Functionality; 3 Experiments; 4 Results; 5 Conclusion; References; How Testable Are BDI Agents? An Analysis of Branch Coverage; 1 Introduction; 2 Belief-Desire-Intention (BDI) Agents; 3 All-Edge Coverage Analysis; 3.1 Removing Failure Handling; 3.2 Simplifying for Uniform Programs

• 4 All-Edges vs. All-Paths5 BDI vs. Procedural; 6 Conclusion; References; Dynamics of Fairness in Groups of Autonomous Learning Agents; 1 Introduction; 2 Multiplayer Ultimatum Game; 2.1 Sub-game Perfect Equilibrium; 3 Learning Model; 4 Results; 5 Discussion and Conclusion; References; Using Stackelberg Games to Model Electric Power Grid Investments in Renewable Energy Settings; 1 Introduction; 2 Related Work; 3 Curtailment Rules; 3.1 Effects of Curtailment Strategies on Renewable Capacity Utilisation
• An Illustration; 4 Renewable Investment in Single Locations

• 4.1 Individual Generator Incentives4.2 Total Generation Capacity; 5 Transmission Investment in Multiple Locations; 5.1 Implementation in Areas with High Curtailment; 5.2 Transmission Investment as a Stackelberg Game; 6 Network Upgrade Case Study; 7 Conclusions and Future Work; References; Multi-scale Simulation for Crowd Management: A Case Study in an Urban Scenario; 1 Introduction; 2 Related Works; 3 A Multi-scale Model for the Simulation of Urban Scenarios; 3.1 The Discrete Microscopic Model; 3.2 The Mesoscopic Model; 3.3 Strategic Model; 4 Analysis of an Urban Scenario

This book features a selection of best papers from 11 workshops held at the International Conference on Autonomous Agents and Multiagent Systems, in Singapore in May 2016. The 11 full papers were carefully reviewed and selected for inclusion in this volume. They cover specific topics, both theoretical and applied, in the general area of autonomous agents and multiagent systems.

• A Language for Trust Modelling (TRUST workshop)
• Abstraction Methods for Solving Graph-Based Security Games (SECMAS workshop)
• Can I Do That? Discovering Domain Axioms Using Declarative Programming and Relational Reinforcement Learning (ARMS workshop)
• Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network (OPTMAS workshop)
• POMDPs for Assisting Homeless Shelters
• Computational and Deployment Challenges (IDEAS workshop)
• Summarizing simulation results using causally-relevant states (MABS workshop)
• Augmenting Agent Computational Environments with Quantitative Reasoning Modules and Customisable Bridge Rules (EMAS workshop)
• Using Awareness to Promote Richer, More Human-Like Behaviors in Artificial Agents (ALA workshop)
• Using GDL to Represent Domain Knowledge for Automated Negotiations (ACAN workshop)
• Simulating Urban Growth with Raster and Vector models: A case study for the city of Can Tho, Vietnam (ABMUS workshop)
• Gamification of Multi-Agent Systems Theory Classes (COIN/CARE workshop)
• Analysis of Market Trend Regimes for March 2011 USDJPY Exchange Rate Tick Data (WEIN workshop).

This book constitutes the most visionary papers of the AAMAS 2016 Workshops, held in Singapore, Singapore, in May 2016. The 12 revised full papers presented were carefully reviewed and selected from the 12 workshops. They cover specific topics, both theoretical and applied, in the general area of autonomous agents and multiagent systems.

• Urban Systems Modelling.- Towards an Agent-Based Simulation of Housing in Urban Beirut.- Simulating Urban Growth with Raster and Vector models: A case study for the city of Can Tho, Vietnam.- Integrating Behavior and Microsimulation Models.- Agent-Based Modelling for Urban Planning Current Limitations and Future Trends.- Traffic Simulation in Urban Modelling.- Software Architecture for a Transparent and Versatile Traffic Simulation.- A Generic Software Framework for Carsharing Modelling based on a Large-Scale Multi-Agent Traffic Simulation Platform.- Mapping bicycling patterns with an agent-based model, census and crowdsourced data.- Transportation in Agent-Based Urban Modelling.- Applications.- Simulation-aided Crowd Management: a Multi-scale Model for an Urban Case Study.- A National Heat Demand Model for Germany.- How Smart is the Smart City? Assessing the Impact of ICT on Cities.
• (source: Nielsen Book Data)

This book constitutes revised, selected, and invited papers from the First International Workshop on Agent Based Modelling of Urban Systems, ABMUS 2016, held in conjunction with AAMAS 2016 in Singapore in May 2016. The 11 papers presented in this volume were carefully reviewed and selected from 20 submissions. They were organized in topical sections named: urban systems modeling; traffic simulation in urban modeling; and applications. .
(source: Nielsen Book Data)

• Mathematical Modeling and Theory
• Fractal Dimension
• A Spatial and Visual Design Technique for the Creation of Lifelike Artificial Forms
• Using Closed Sets to Model Cognitive Behavior
• Learning and Optimization
• Solving dynamic optimisation problem with known changeable boundaries
• Compaction for Code Fragment Based Learning Classifier Systems
• The Boon of Gene-Culture Interaction for Effective Evolutionary Multitasking
• A Study on Performance Metrics to Identify Solutions of Interest From a Trade-off Set
• Dynamic Configuration of Differential Evolution Control Parameters and Operators
• Exploring the Feasible Space using Constraint Consensus in Solving Constrained Optimization Problems
• A Nested Differential Evolution based Algorithm for Solving Multi-objective Bilevel Optimization Problems
• Parkinson's Disease Data Classification Using Evolvable Wavelet Neural Networks
• GO-PEAS: A Scalable Yet Accurate Grid-based Outlier Detection Method Using Novel Pruning Searching Techniques
• Multi-objective Genetic Programming for Figure-ground Image Segmentation
• A New Modification of Fuzzy C-Means via Particle Swarm Optimization for Noisy Image Segmentation
• Competitive Island Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction
• Reverse Neuron Level Decomposition for Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction
• A Delaunay Triangulation Based Density Measurement for Evolutionary Multi-objective Optimization
• Use of Infeasible Solutions During Constrained Evolutionary Search: A Short Survey
• Planning and Scheduling
• A Differential Evolution Algorithm for Solving Resource Constrained Project Scheduling Problems
• A hybrid imperialist competitive algorithm for flexible job shop problem
• Parallel Multi-objective Job Shop Scheduling Using Genetic Programming
• Optimization of Location Allocation of Web Services Using A Modified Non-dominated Sorting Genetic Algorithm
• Double Action Genetic Algorithm for Scheduling the Wind-Thermal Generators
• Feature Selection
• Investigating Multi-operator Differential Evolution for Feature Selection
• Coevolutionary Feature Selection and Reconstruction in Neuro-Evolution for Time Series Prediction
• A Subset Similarity Guided Method for Multi-objective Feature Selection
• Applications and Games
• An Evolutionary Optimization Approach to Maximize Runway Throughput Capacity for Hub and Spoke Airports
• Finite Population Trust Game Replicators
• Towards Evolved Time to Contact Neurocontrollers for Quadcopters
• The Effect of Risk Perceived Payoffs in Iterated Interdependent Security Games
• Genetic Algorithm Based Trading System Design.

This book constitutes the proceedings of the Second Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2016, held in Canberra, ACT, Australia, in February 2016. The 30 full papers presented in this volume were carefully reviewed and selected from 41 submissions. They are organized in topical sections named: mathematical modeling and theory; learning and optimization; planning and scheduling; feature selection; and applications and games.

• Artificial Life and Computational Intelligence.- Extending the Delaunay Triangulation Based Density Measurement to Many-objective Optimization.- Emotion, Trustworthiness and Altruistic Punishment in a Tragedy of the Commons Social Dilemma.- Equity Option Strategy Discovery and Optimization Using a Memetic Algorithm.- Co-Evolving Line Drawings with Hierarchical Evolution.- Reliability estimation of individual multi-target regression predictions.- Feedback Modulated Attention Within a Predictive Framework.- A Batch Infill Strategy for Computationally Expensive Optimization Problems.- Automatic Clustering and Summarisation of Microblogs: A Multi-Subtopic Phrase Reinforcement Algorithm.- Generation and exploration of architectural form using a composite Cellular Automata.- Wrapper Feature Construction for Figure-ground Image Segmentation Using Genetic Programming.- Surrogate-assisted Multi-swarm Particle Swarm Optimization of Morphing Airfoils.- Applying Dependency Patterns in Causal Discovery of Latent Variable Models.- An Evolutionary Multi-criteria Journey Planning Algorithm for Multi-modal Transportation Networks.- Estimating Passenger Preferences Using Implicit Relevance Feedback for Personalized Journey.- Quantitative Assessment of Hearts Function: A Hybrid Mechanism for Left Ventricles Segmentation from Cine MRI Sequences.- A Hybrid feature selection scheme based on local compactness and global separability for improving roller bearing diagnostic performance.- Reliable Fault Diagnosis of Bearings Using Distance and Density Similarity on an Enhanced k-NN.- Towards Solving TSPN with Arbitrary Neighborhoods: A Hybrid Solution.- Detectable Genetic Algorithms-based techniques for solving Dynamic Optimisation Problem with Unknown Active Variables.- Neighbourhood analysis: a case study on Google Machine Reassignment Problem.- Optimisation Algorithms and Applications.- Multi-Objective Optimisation with Multiple Preferred Regions.- An Adaptive Memetic Algorithm for the Architecture Optimisation Problem.- Resource Constrained Job Scheduling with Parallel Constraint-based ACO.- An Iterated Local Search with Guided Perturbation for the Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Three-Dimensional Loading Constraints.- A Memetic Cooperative Co-evolution Model for Large Scale Continuous Optimization.- Investigating the Generality of Genetic Programming based Hyper-heuristic Approach to Dynamic Job Shop Scheduling with Machine Breakdown.- Exploratory Analysis of Clustering Problems Using a Comparison of Particle Swarm Optimization and Differential Evolution.- A PSO-based Reference Point Adaption Method for Genetic Programming Hyper-heuristic in Many-Objective Job Shop Scheduling.- Optimal power allocation of wireless sensor networks with multi-operator based constrained differential evolution.- CEMAB: A Cross-Entropy-based Method for Large-Scale Multi-Armed Bandits.- Binary PSO for Web Service Location-Allocation.- A MOEA/D with Non-uniform Weight Vector Distribution Strategy for Solving the Unit Commitment Problem in Uncertain Environment.
• (source: Nielsen Book Data)

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 submissions. They were organized in topical sections named: artificial life and computational intelligence and optimization algorithms and applications. .
(source: Nielsen Book Data)

• Chapter 1. GUI Testing for Introductory Object-Oriented Programming Exercises (Ushio Inoue).-
• Chapter 2. Python Deserialization Denial of Services Attacks and their Mitigations (Kousei Tanaka).-
• Chapter 3. A Branch-and-Bound Based Exact Algorithm for the Maximum Edge-Weight Clique Problem (Satoshi Shimizu).-
• Chapter 4. A Software Model for Precision Agriculture Framework Based on Smart Farming System and Application of IoT Gateway (Symphorien Karl Yoki Donzia).-
• Chapter 5. Components of Mobile Integration in Social Business and E-commerce Application (Mechelle Grace Zaragoza).
• (source: Nielsen Book Data)

This book presents the outcomes of the 5th ACIS International Conference on Computational Science/Intelligence & Applied Informatics (CSII 2018), which was held on July 10-12, 2018 in Yonago, Japan. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here. The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conference's most promising papers were selected for this Springer (SCI) book. We eagerly await the important contributions that we know these authors will make to the field of computer and information science.
(source: Nielsen Book Data)