AI 2021: Advances in Artificial Intelligence [electronic resource] : 34th Australasian Joint Conference, AI 2021, Sydney, NSW, Australia, February 2–4, 2022, Proceedings /

Ethical AI -- An Explanation Module for Deep Neural Networks Facing Multivariate Time Series Classification -- Privacy-preserving in Double Deep-Q-Network with differential privacy in Continuous Spaces -- HESIP: a Hybrid System for Explaining Sub-symbolic Predictions -- An Explainable Recommendation Based on Acyclic Paths in an Edge-Colored Graph -- Knowledge Transfer for Deep Reinforcement Agents in General Game Playing -- GSMI: A Gradient Sign Optimization Based Model Inversion Method -- Multicollinearity Correction and Combined Feature Effect in Shapley Values -- Does a Face Mask Protect my Privacy? Using Deep Learning to Predict Protected Attributes from Masked Face Images -- Representation-Induced Algorithmic Bias: An empirical assessment of behavioural equivalence over 14 reinforcement learning algorithms across 4 isomorphic gameform representations -- Contextual Importance and Utility: a Theoretical Foundation -- Deeper Insights into Neural Nets with Random Weights -- Applications -- De Novo Molecular Generation with SBiAAE -- Tailoring Contact Based Scoring Functions for Protein Structure Prediction -- Evaluation of Deep Learning Techniques on a Novel Hierarchical Surgical Tool Dataset -- Feature Extraction Using Wavelet Scattering Transform Coefficients for EMG Pattern Classification -- Modelling Eye-gaze Movement using Gaussian Auto-regression Hidden Markov -- Strategies Improve Social Welfare: An Empirical Study of Strategic Voting in Social Networks -- A Network-based Rating Mechanism Against False-Name Attack -- Modular Construction Planning using Graph Neural Network Heuristic Search -- Priority-based Traffic Management Protocol for Autonomous Vehicles on Road Network -- Improving Traffic Load Prediction with Multi-Modality: A Case Study of Brisbane -- Predicting Geological Material Types with Ground Penetrating Radar -- A Gated Recurrent Neural Network for Electric Vehicle Detection with Imbalanced Samples -- User-Defined Smart Contracts using Answer Set Programming -- Predicting Financial Literacy via Semi-supervised Learning -- Machine Teaching-based Efficient Labelling for Cross-unit Healthcare Data Modelling -- Predicting COVID-19 Patient Shielding: A Comprehensive Study -- Machine learning algorithms in application to COVID-19 severity prediction in patients -- Identifying the effective restriction and vaccination policies during the COVID-19 crisis in Sydney: A machine learning approach -- Beyond Topics: Discovering Latent Healthcare Objectives from Event Sequences -- Predicting Outcomes for Cancer Patients with Transformer-based Multi-task Learning -- Deep Reinforcement Learning for DynamicThings of Interest Recommendation in Intelligent Ambient Environment -- A Self-Learning Approach for Baggiatoa Coverage Estimation in Aquaculture -- Real-time prediction of the lane-based delay for group-based adaptive traffic operations using Long Short-Term Memory -- Exploring Transformers for Intruder Detection in Complex Maritime Environment -- Transfer Learning Assisted GPHH for Dynamic Multi-Workflow Scheduling in Cloud Computing -- Automated Image Classification in the Diagnosis of Knee MRI -- Classical AI -- Analysing multiobjective optimization using evolutionary path length correlation -- Decentralizing Self-organizing Maps -- A heuristic repair algorithm for the maximum stable marriage problem with ties and incomplete lists -- The Hierarchical Discrete Learning Automaton Suitable for Environments with Many Actions and High Accuracy Requirements -- Hybrid Grouping Genetic Algorithm for Large-scale Two-Level Resource Allocation of Containers in the Cloud -- Transfer Learning for Autonomous Recognition of Swarm Behaviour in UGVs -- Multivariate Ordinal Patterns for Symmetry Approximation in Dynamic Probabilistic Relational Models -- A Hybrid Multiagent-based Rescheduling Mechanism for Open and Stochastic Environments Concerning the Execution Stage -- BiES: Adaptive Policy Optimization for Model-based Offline Reinforcement Learning -- Improvement of Arc Consistency in Asynchronous Forward Bounding algorithm -- Computer Vision and Machine Learnin -- GAN-Assisted YUV Pixel Art Generation -- Investigating Active Positive-Unlabeled Learning with Deep Networks -- UFO RPN: A Region Proposal Network for Ultra Fast Object Detection -- Accurate New Zealand Wildlife Image Classification- Deep learning approach -- Better Self-training for Image Classification through Self-supervision -- Video-based Student Engagement Estimation via Time Convolution Neural Networks for Remote Learning -- Eye Movement and Visual Target Synchronization Level Detection Using Deep Learning -- Vehicle Detection Based on Cascade Deep Learning Method Using Deformed Oriented Bounding Box -- Improving Evolutionary Generative Adversarial Networks -- Natural Language Processing and Data Mining -- Focus-based Text Summarization with Hybrid Embeddings -- An Empirical Study of Fuzzy Decision Tree for Gradient Boosting Ensemble -- SimSCL : A Simple fully-Supervised Contrastive Learning Framework for Text Representation -- KPCR: Knowledge graph enhanced Personalized Course Recommendation -- Probabilistic Term Weighting based on Three-Way Decisions for Class Based Feature Selection -- LTWNN: A Novel Approach using Sentence Embeddings for Extracting Diverse Concepts in MOOCs -- ETBTRank: Ranking Biterms in Paper Titles for Emerging Topic Discovery -- Network Analysis -- Inference of Geological Material Groups Using Structural Monitoring Sensors on Excavators.

This book constitutes the proceedings of the 34th Australasian Joint Conference on Artificial Intelligence, AI 2021, held in Sydney, NSW, Australia, in February 2022.* The 64 full papers presented in this volume were carefully reviewed and selected from 120 submissions. The papers were organized in topical sections named: Ethical AI, Applications, Classical AI, Computer Vision and Machine Learning, Natural Language Processing and Data Mining, and Network Analysis. *The conference was postponed from December 2021 to February 2022 and held virtually due to the COVID-19 pandemic.