Preface
Organization
Abstracts of Invited Speakers
Responsible AI: From Principles to Action
Trustworthy Human-Centric AI – The European Approach
Multimodal Simultaneous Machine Translation
Factored Value Functions for Cooperative Multi-agent Reinforcement Learning
Contents
Artificial Intelligence and IoT in Agriculture
Autonomous Robot Visual-Only Guidance in Agriculture Using Vanishing Point Estimation
1 Introduction
2 Related Work
3 Visual Steering on Agriculture: The Main Approach
3.1 Hardware
3.2 Vanishing Point Detection
3.3 Autonomous Guidance
4 Results
4.1 Methodology
4.2 Base Trunk Detection
4.3 Vanishing Point Estimation
4.4 Autonomous Guidance Performance
5 Conclusions
References
Terrace Vineyards Detection from UAV Imagery Using Machine Learning: A Preliminary Approach
1 Introduction
2 Background
2.1 UAV Sensors
2.2 Machine Learning in Agriculture
3 Materials and Methods
3.1 UAV Data Acquisition and Processing
3.2 Dataset
3.3 Machine Learning Approach
3.4 Classifier
4 Results and Discussion
5 Conclusions and Future Work
References
Tomato Detection Using Deep Learning for Robotics Application
1 Introduction
2 State of the Art
3 Materials and Methods
3.1 Data Acquisition and Processing
3.2 Training and Evaluating DL Models
4 Results and Discussion
5 Conclusion
References
Predicting Predawn Leaf Water Potential up to Seven Days Using Machine Learning
1 Introduction
2 Background Concept
3 Materials and Methods
3.1 Experimental Field
3.2 Data Visualization and Summarization
3.3 Problem Definition and Feature Engineering
4 Experiments
4.1 Fill the Gaps
4.2 Seven Days Prediction
5 Results and Discussion
5.1 Algorithms Comparison and Variable Importance
5.2 Models Validation
5.3 Error Analysis
6 Conclusion and Future Work
6.1 Future Work
References
Artificial Intelligence and Law
Towards Ethical Judicial Analytics: Assessing Readability of Immigration and Asylum Decisions in the United Kingdom
1 Introduction
2 Assessing Readability, and Judicial Analytics
2.1 Development and Critique of Readability Formulas
2.2 Previous Work Assessing the Readability of Legal Texts
2.3 Potential Pitfalls of Judicial Analytics
2.4 Lessons from the Literature
3 Ethical Judicial Analytics
3.1 Replicating Previous Work
3.2 Dataset and Analysis
3.3 Results
3.4 Interpretation and Critical Discussion of Results
3.5 Addressing Limitations of Standard Readability Formulas Through the Use of ML Approaches
3.6 Ethical Considerations in Judicial Analytics
4 Conclusions: Developing Ethical Judicial Analytics in Service of the Stakeholders of the Legal System
References
A Comparison of Classification Methods Applied to Legal Text Data
1 Introduction
2 Related Work
3 Theoretical Basis
3.1 Artificial Neural Networks
3.2 Dropout
3.3 Support Vector Machine
3.4 K-Nearest Neighbors
3.5 Naive Bayes
3.6 Decision Tree
3.7 Random Forest
3.8 Adaboost
3.9 Term Frequency - Inverse Document Frequency
4 Methodology
4.1 Type of Study
4.2 Dataset
4.3 Evaluation Measures
4.4 Machine Learning Pipeline
5 Results
6 Conclusions
References
Artificial Intelligence in Medicine
Aiding Clinical Triage with Text Classification
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Available Data
3.2 Task
3.3 Dataset
3.4 Text Representation
3.5 Experiments
3.6 Experimental Setup
4 Results
4.1 Find the Best'' Algorithm and Representation
4.2 Fine-Tuning the Embedding Model
4.3 Considering the Most Probable Clinical Pathways
5 Discussion
6 Conclusions
References
A Web-based Telepsychology Platform Prototype Using Cloud Computing and Deep Learning Tools
1 Introduction
2 Description of the System
2.1 Cloud-Based Backend Software Architecture
2.2 Web Client as Frontend
2.3 Biomedical Parameters Acquisition
3 Results
4 Conclusions and Future Work
References
Detecting, Predicting, and Preventing Driver Drowsiness with Wrist-Wearable Devices
1 Introduction
2 Related Work
2.1 Measurement of Driver Drowsiness
2.2 Drowsiness Detection
2.3 Drowsiness Prediction
2.4 Sleep Staging
3 Methodology
4 Results
5 Conclusion
References
The Evolution of Artificial Intelligence in Medical Informatics: A Bibliometric Analysis
1 Introduction
2 A Brief History of AI in Healthcare
3 Related Work
4 Methodology
5 Results
6 Discussion
7 Conclusion
References
Artificial Intelligence in Power and Energy Systems
Optimizing Energy Consumption of Household Appliances Using PSO and GWO
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 Swarm Intelligence Optimization Algorithms
3.2 Mathematical Model
4 Case Study
5 Results and Discussion
6 Conclusions
References
Metaheuristics for Optimal Scheduling of Appliances in Energy Efficient Neighbourhoods
1 Introduction
2 Related Work
3 Problem Definition
3.1 Representation of the Solution and Objective Function
3.2 Constraints
3.3 Search Space
3.4 Algorithms for Solving the Problem
4 Experimental Setup
5 Results and Discussion
6 Conclusion
References
Multitask Learning for Predicting Natural Flows: A Case Study at Paraiba do Sul River
1 Introduction
2 Materials and Methods
2.1 Study Area and Data
2.2 Streamflow Estimation Model
3 Computational Experiments
4 Conclusion
References
PV Generation Forecasting Model for Energy Management in Buildings
1 Introduction
2 SCADA System
3 Solar Forecasting Model
4 Case Study
5 Conclusions
References
Automatic Evolutionary Settings of Machine Learning Methods for Buildings' Thermal Loads Prediction
1 Introduction
2 Methods
2.1 Dataset
2.2 Machine Learning Methods
2.3 Model Selection Based on Differential Evolution
3 Computational Experiments
4 Conclusion
References
Artificial Intelligence in Transportation Systems
Minimising Fleet Times in Multi-depot Pickup and Dropoff Problems
1 Introduction
2 Related Work
3 Preliminaries for MDPDPs
3.1 Routing Plans
3.2 Fleet Objectives
4 New Datasets for MDPDPs
5 Genetic Template for MDPDPs
6 Experiments for MDPDPs
6.1 Objective Values
6.2 Sharing Rates
6.3 Fleet Busyness
6.4 Fleet Size
7 Conclusions
References
Solving a Bilevel Problem with Station Location and Vehicle Routing Using Variable Neighborhood Descent and Ant Colony Optimization
1 Introduction
2 Related Work
3 Bilevel Problem: Station Location and Vehicle Routing
4 Proposed Bilevel Approach
4.1 Variable Neighborhood Descent for Station Allocation
4.2 Ant Colony Optimization for Routing Planning
4.3 Local Search Procedures and Route Selection
5 Computational Experiments
5.1 Analysis of the Results
6 Concluding Remarks and Future Works
References
Artificial Life and Evolutionary Algorithms
Genetic Programming for Feature Extraction in Motor Imagery Brain-Computer Interface
1 Introduction
2 The Clinical Brain-Computer Interface Dataset
3 Data Preprocessing
3.1 Band-Pass Filter
3.2 Wavelet Transform
4 Sigmoid Single Electrode Energy
5 Genetic Programming
6 Proposed Single Feature Genetic Programming
7 Computational Experiments
7.1 Dimension of the Problem
8 Conclusions
References
FERMAT: Feature Engineering with Grammatical Evolution
1 Introduction
2 Related Work
2.1 AutoML - Automated Machine Learning
2.2 Structured Grammatical Evolution
2.3 Drug Development
3 FERMAT
4 Experimental Settings
5 Results
5.1 Feature Engineering
5.2 Absolute Performance
6 Conclusions
References
Ambient Intelligence and Affective Environments
A Reputation Score Proposal for Online Video Platforms
1 Introduction
2 Related Works
2.1 Commercial Proposals
2.2 Academic Proposals
3 The Platform
4 Implementation
4.1 Essential Factors
4.2 Mapping Functions
4.3 Defined Metrics
4.4 Generalisation Potential and Risks
5 Conclusions and Future Work
References
A Reinforcement Learning Approach to Improve User Achievement of Health-Related Goals
1 Introduction
2 Proposed Model
2.1 Personal Agent
2.2 Coaching Agent
3 Results and Discussion
4 Conclusions and Future Work
References
Urban Human Mobility Modelling and Prediction: Impact of Comfort and Well-Being Indicators
1 Introduction
2 State of the Art
2.1 Crowdsensing Infrastructures
2.2 Well-Being and Comfort
3 Experimental Case Study
3.1 Data Collection
3.2 Data Pre-processing
3.3 Building the Models
3.4 Results
4 Discussion
5 Conclusions
References
Comparison of Transfer Learning Behaviour in Violence Detection with Different Public Datasets
1 Introduction
2 State of Art
2.1 RGB Based
3 Methodology and Methods
3.1 Architecture Networks
3.2 Dataset
3.3 Training Settings
4 Results and Discussion
5 Conclusion and Future Work
References
General AI
Deep Neural Network Architectures for Speech Deception Detection: A Brief Survey
1 Introduction
2 Methodology
3 Speech Deception Detection Features
4 Deep Learning Methods to Speech Deception Detection
4.1 Long Short-Term Memory
4.2 Hybrid Networks
5 Discussions
6 Conclusions and Future Works
References
3DSRASG: 3D Scene Retrieval and Augmentation Using Semantic Graphs
1 Introduction
2 3DSRASG: System Design
2.1 Block Diagram
2.2 Dataset Preprocessing
2.3 Reinforcement Learning Using Gaussian Mixture Model
2.4 Speech Processing
2.5 Text Processing
2.6 Semantic Scene Graph Generation
2.7 Scene Extraction and Enhancement
3 Results
4 Conclusion
References
RevisitingRecurrent World Models Facilitate Policy Evolution''
1 Introduction
2 Background
2.1 Variational Autoencoders
2.2 MDN-RNN
2.3 Controller
3 Comparative Analysis
3.1 Replicating HS
3.2 Perceptual Model
3.3 Ablation Study
3.4 Training Policy
4 Conclusion and Future Work
A Full Comparative Results
A.1 Ablation Study Additional Results
A.2 Improved Sample Policy
B Model details
B.1 VAE
B.2 MDN-RNN
B.3 Controller
B.4 Hyperparameters
References
Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL
1 Introduction
2 Background
2.1 C-SPARQL
2.2 Neural Networks for Time Series Classification
3 Methodology
3.1 Dataset
3.2 C-SPARQL Queries
3.3 Training RNNs and CNNs
4 Experiments and Results
4.1 Queries with Temporal Events
4.2 Queries with Background Knowledge
4.3 Combining Temporal Events and Background Knowledge
5 Conclusions
References
The DeepONets for Finance: An Approach to Calibrate the Heston Model
1 Introduction
2 Problem Formulation
2.1 Related Work
2.2 The Heston Model
2.3 The Deep Operator Networks - DeepONets
3 Method
4 Results and Discussion
5 Conclusion
References
Faster Than LASER - Towards Stream Reasoning with Deep Neural Networks
1 Introduction
2 Background
2.1 Laser
2.2 Neural Networks
3 Methods
3.1 Dataset
3.2 LASER Queries
3.3 Training and Testing CNNs and RNNs
4 Description of Experiments and Results
4.1 Test Case 1
4.2 Test Case 2
4.3 Test Case 3
4.4 Test Case 4
4.5 Test Case 5
5 Conclusions
References
Using Regression Error Analysis and Feature Selection to Automatic Cluster Labeling
1 Introduction
2 Related Works
3 Cluster Labeling Model
3.1 Step I—Definition of Attribute–Range Pairs
3.2 Step II
4 Experimental Methodology
5 Results
6 Conclusion
References
A Chatbot for Recipe Recommendation and Preference Modeling
1 Introduction
2 Background
3 Methodology
3.1 Intent Classification and Entity Recognition
3.2 Preference Modeling
3.3 Food Matching
3.4 Dialogue Management
4 User Validation
4.1 Results
5 Conclusions
References
Intelligent Robotics
Exploiting Symmetry in Human Robot-Assisted Dressing Using Reinforcement Learning
1 Introduction
2 Background
3 Problem Formulation with Symmetry Based-Approach
3.1 MDP Model
3.2 Reinforcement Learning
3.3 Extending MDPs with Symmetry
4 Experimental Procedure
4.1 Experimental Setup
4.2 Kinesthetic Learning
4.3 Probabilistic Human Displacement Model
4.4 Cost Estimation
5 Evaluation and Results
5.1 Policy Learning in Simulation
5.2 Real-World Evaluation with a Robotic Platform
6 Conclusions
References
I2SL: Learn How to Swarm Autonomous Quadrotors Using Iterative Imitation Supervised Learning
1 Introduction
2 Methodology
2.1 Flocking Algorithm
2.2 Iterative Imitation Supervised Learning
3 A Proof of Principle of I2SL: Application to Quadrotors Control
3.1 Position of the Problem
3.2 Data Acquisition
3.3 Forward Model
3.4 I2SL Controller
4 Experimental Setting
4.1 Goals of Experiments
4.2 Baseline
4.3 Simulation Platform
4.4 Learning of the Flocking Model
5 Empirical Validation
5.1 Zigzag Experiment
6 Discussion and Future Work
References
Neural Network Classifier and Robotic Manipulation for an Autonomous Industrial Cork Feeder
1 Introduction
2 Implementation
2.1 System Overview
2.2 Conveyor Belt and Inspection Tunnel
2.3 Computer Vision
2.4 Cork Detection
2.5 Neural Network
2.6 Robot Arm
2.7 Gripper
2.8 Robot Arm Movement Controller
3 Results and Analysis
4 Conclusion and Future Work
References
NOPL - Notification Oriented Programming Language - A New Language, and Its Application to Program a Robotic Soccer Team
1 Introduction
2 Notification Oriented Programming
3 The Notification Oriented Programming Language
4 Case Study - Control of 6 Robots for the Small Size League (SSL) Category - In Simulation
5 Experimental Results
6 Conclusions
References
Compound Movement Recognition Using Dynamic Movement Primitives
1 Introduction
2 Recognition and Prediction Using Critical Points
2.1 Motion Recognition
2.2 Motion Prediction
3 Recognition and Prediction of Compound Movements
3.1 Motion Recognition
3.2 Motion Prediction
4 Experiments and Results
4.1 Recognition
4.2 Prediction
4.3 Accuracy
4.4 Improving the Knowledge of the Robot
4.5 Experiment with Robot
5 Conclusion
References
Metaheuristics for the Robot Part Sequencing and Allocation Problem with Collision Avoidance
1 Introduction
2 Related Literature
3 The Part Sequencing and Allocation Problem
4 Solving the Routing Problem
5 The Parts Sequencing and Allocation Metaheuristic Algorithm
6 Sensitivity Analysis
7 Conclusion
References
Knowledge Discovery and Business Intelligence
Generalised Partial Association in Causal Rules Discovery
1 Introduction
2 Background
2.1 Association Rule Mining
2.2 Cochran-Mantel-Haenszel Test
2.3 Uncertainty Coefficient
3 Causal Association Rules with Partial Association and Uncertainty Coefficient
3.1 An Illustrative Example
4 Results and Discussion
4.1 Pattern Metrics Evaluation
4.2 Prediction
5 Conclusion
References
Dynamic Topic Modeling Using Social Network Analytics
1 Introduction
2 Related Work
3 Case Study
4 Methodology
4.1 Problem Description
4.2 Hashtag Co-occurrence Network
4.3 Stream Sampling
4.4 Community Detection
5 Experimental Evaluation
5.1 Results Discussion
6 Conclusion and Future Work
References
Imbalanced Learning in Assessing the Risk of Corruption in Public Administration
1 Introduction
2 Data Enrichment and Data Cleansing
3 Imbalanced Learning
3.1 Synthetic Minority Oversampling Technique (SMOTE)
3.2 Logistic Regression
4 Computational Results
4.1 Data-Level Solutions
4.2 Algorithm-Level Solutions
5 Discussion
6 Conclusions
References
Modelling Voting Behaviour During a General Election Campaign Using Dynamic Bayesian Networks
1 Introduction
2 Background
3 Data
3.1 Data Collection
3.2 Participants
3.3 Variables
3.4 Data Modelling
3.5 Comparison of Models
4 Results and Discussion
5 Conclusion
References
ESTHER: A Recommendation System for Higher Education Programs
1 Introduction
2 Literature Review
2.1 Recommendation Systems in Education
3 Recommendation System for Higher Education Programs
3.1 Requirements Specification
3.2 Knowledge Domain
3.3 Architecture
4 Preliminary Results
5 Conclusions
References
A Well Lubricated Machine: A Data Driven Model for Lubricant Oil Conditions
1 Introduction
2 Related Work
3 Data Collection
4 Experimental Study
4.1 Dataset
4.2 Prediction Model
4.3 Evaluation Metrics
5 Results
6 Conclusion
References
A Comparison of Machine Learning Methods for Extremely Unbalanced Industrial Quality Data
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Data
3.2 Balancing Methods
3.3 Machine Learning Algorithms
3.4 Evaluation
4 Results
5 Conclusions
References
Towards Top-Up Prediction on Telco Operators
1 Introduction
2 Methodological Approach
2.1 Data Set Analysis
2.2 Building and Selecting Features
2.3 Sliding Window Regression
3 Experiments and Results
3.1 Data Set
3.2 Parameterization
4 Conclusion and Future Work
References
Biomedical Knowledge Graph Embeddings for Personalized Medicine
1 Introduction
1.1 Personalized Medicine
2 Methods
2.1 Knowledge Graph
2.2 Knowledge Graph Embeddings
2.3 Clustering
3 Results and Discussion
3.1 Knowledge Graph Embedding
3.2 Use Case: Prediction of Gene-Disease Associations
3.3 Use Case: Autism Spectrum Disorder (ASD) Disease Clusters
4 Conclusions
References
Deploying a Speech Therapy Game Using a Deep Neural Network Sibilant Consonants Classifier
1 Introduction
2 Serious Game for Sigmatism and EP Sibilant Consonants
3 Sibilants Classifier
4 Results for the Deployed Architecture
4.1 Silence Detection
4.2 PythonAnywhere Performance
4.3 CNN Optimization
5 Discussion
6 Conclusions and Future Work
References
Data Streams for Unsupervised Analysis of Company Data
1 Introduction
2 Non-supervised Data Analysis, Advanced Data Exploration and Visualization Tools
2.1 UbiSOM Concepts and Stream Learning Metrics
3 Experimental Setup
3.1 SOM Training
3.2 SOM Analysis
4 Related Work
5 Conclusions
References
Multi-agent Systems: Theory and Applications
One Arm to Rule Them All: Online Learning with Multi-armed Bandits for Low-Resource Conversational Agents
1 Introduction
2 From Prediction with Expert Advice to Multi-armed Bandits
3 Related Work
4 Proof-of-Concept: Retrieval-Based Conversational Agent with Multi-armed Bandits
4.1 Finding the Best Answer Selection Criteria
4.2 Obtaining User Feedback
5 Experimental Results
6 Conclusions and Future Work
References
Helping People on the Fly: Ad Hoc Teamwork for Human-Robot Teams
1 Introduction
2 Notation and Background
3 Bayesian Online Prediction for Ad Hoc Teamwork
3.1 Assumptions
3.2 Preliminaries
3.3 Bayesian Online Prediction for Ad Hoc Teamwork (BOPA)
4 Evaluation
4.1 Evaluation Procedure
4.2 Metrics
5 Results
5.1 PB Scenario
5.2 ER Scenario
6 Conclusion and Future Work
References
Ad Hoc Teamwork in the Presence of Non-stationary Teammates
1 Introduction
2 Related Work
3 PLASTIC Policy with Adversarial Selection
3.1 Architecture
4 Experimental Evaluation
4.1 Experimental Setup
4.2 Results
5 Conclusions and Future Work
References
Carbon Market Multi-agent Simulation Model
1 Introduction
1.1 Carbon Tax
1.2 Multi-agent Based Simulation
2 Model Formalization
2.1 The Model
2.2 The Agents
2.3 Simulation Stages
3 Experiments and Results
3.1 Scenario 1 - Auction Market
3.2 Scenario 2 - Carbon Tax
4 Conclusions and Future Work
References
Cloud Based Decision Making for Multi-agent Production Systems
1 Introduction
2 Background
3 Decision Making Framework
3.1 Multi-agent System (MAS) Component
3.2 Cloud Computing Component
4 Experimentation and Deployment
4.1 Cloud-Based Decision Making
4.2 Multi-agent Based Simulation
5 Conclusion and Future Work
References
A Data-Driven Simulator for Assessing Decision-Making in Soccer
1 Introduction
2 Related Work
3 Simulator
3.1 Data
3.2 Models
4 Results
4.1 Simulating Sequences of Play
4.2 Building Playing Criterion
4.3 Reinforcement Learning
5 Conclusion
5.1 Future Work
References
Text Mining and Applications
CyberPolice: Classification of Cyber Sexual Harassment
1 Introduction
2 Related Work
3 Dataset
3.1 Data Scraping
3.2 Data Cleaning and Data Labelling
4 Model Architectures
4.1 ML Classifiers
4.2 CNN Model
4.3 LSTM Model
4.4 BiLSTM Model
4.5 CNN-BiLSTM Model
4.6 ULMFiT Model
4.7 BERT Model
5 Experiment Setup
6 Results
7 Conclusion
References
Neural Text Categorization with Transformers for Learning Portuguese as a Second Language
1 Introduction
2 Related Work
3 Corpus
4 Transformer Models
4.1 GPT-2
4.2 RoBERTa
5 Implementation
6 Evaluation and Discussion
7 Conclusion
References
More Data Is Better Only to Some Level, After Which It Is Harmful: Profiling Neural Machine Translation Self-learning with Back-Translation
1 Introduction
2 Related Work
3 Methods for Back-Translation
3.1 Beam Search
3.2 Beam Search+Noise
4 Experimental Setup
4.1 NMT Architecture
4.2 Corpora
4.3 Experiments
5 Results
5.1 English German
5.2 Portuguese Chinese
6 Discussion
7 Conclusion
References
Answering Fill-in-the-Blank Questions in Portuguese with Transformer Language Models
1 Introduction
2 Background and Related Work
3 Experimentation Setup
3.1 Data
3.2 Models
4 Answering Fill-in-the-Blank Questions
4.1 Approach
4.2 Results
4.3 Examples
5 Answering Multiple Choice Fill-in-the-Blank Questions
5.1 Approaches
5.2 Results
5.3 Examples
6 Conclusion
References
Cross-Lingual Annotation Projection for Argument Mining in Portuguese
1 Introduction
2 Related Work
3 Corpora
4 Annotation Projection
4.1 Input Data
4.2 Translation
4.3 Alignment
4.4 Projection Algorithm
4.5 Intrinsic Evaluation
5 Extrinsic Evaluation
5.1 Experimental Setup
5.2 Results
6 Conclusions
References
Acceptance Decision Prediction in Peer-Review Through Sentiment Analysis
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Evaluation Dataset
3.2 Data Preprocessing
3.3 Machine Learning Algorithms
3.4 Sentiment Analysis
4 Results
4.1 Paper Acceptance Classification
4.2 Overall Evaluation Score Prediction
4.3 Sentiment Analysis
5 Discussion
6 Conclusions and Future Work
References
Application of Data Augmentation Techniques for Hate Speech Detection with Deep Learning
1 Introduction
2 Related Work
3 Methodology
3.1 Datasets
3.2 Data Pre-processing
3.3 Data Augmentation
3.4 Sentence Encoding
3.5 Architectures
3.6 Experimental Setup
3.7 Measures
4 Results
4.1 Results with CNN
4.2 Results with Parallel CNN
4.3 Results with LSTM
5 Conclusions
References
Automated Fake News Detection Using Computational Forensic Linguistics
1 Introduction
2 Related Work
3 Resources
3.1 Corpora
3.2 Natural Language Processing Resources
4 System Description
4.1 Feature Extraction
4.2 Dataset Description
4.3 Classification Process
5 Experimental Results
5.1 Feature Analysis
6 Conclusions
References
Author Index