Compressing Bayesian Networks: Swarm-Based Descent, Efficiency, and Posterior Accuracy -- De-Causalizing NAT-Modeled Bayesian Networks for Inference Efficiency -- A Novel Evaluation Methodology for Assessing Off-Policy Learning Methods in Contextual Bandits -- Synthesizing Controllers: On the Correspondence Between LTL Synthesis and Non-Deterministic Planning -- Logic-Based Benders Decomposition for Two-Stage Flexible Flow Shop Scheduling with Unrelated Parallel Machines -- Advice-Based Exploration in Model-Based Reinforcement Learning -- Deep Super Learner: A Deep Ensemble for Classification Problem -- One Single Deep Bidirectional LSTM Network for Word Sense Disambiguation of Text Data -- MedFact: Towards Improving Veracity of Medical Information in Social Media Using Applied Machine Learning -- Re-ranking Candidate Lists for Improved Lexical Induction -- Analysis of Social Media Posts for Early Detection of Mental Health Conditions -- Motor Bearing Fault diagnosis Using Deep Convolutional Neural Networks with 2D Analysis of Vibration Signal -- Mobile App for Detection of Counterfeit Banknotes -- A Multi-agent Framework for Understanding Addiction -- Infusing Domain Knowledge to Improve the Detection of Alzheimer's Disease from Everyday Motion Behavior -- An Incremental Machine Learning Algorithm for Nuclear Forensics -- MML-Based Approach for Determining the Number of Topics in EDCM Mixture Models -- Constrained Bayesian Optimization for Problems with Piece-wise Smooth Constraints -- Dimensionality Reduction and Visualization by Doubly Kernelized Unit Ball Embedding -- Accelerated Gradient and Block-wise Gradient Methods for Big Data Factorization -- Learning Belief Revision Operators -- Solving Constraint Satisfaction Problems Using Firey Algorithms -- An AI Planning-Based Approach to the Multi-Agent Plan Recognition Problem -- Predicting Transportation Modes of GPS Trajectories Using Feature Engineering and Noise Removal -- Prediction of Container Damage Insurance Claims for OptimizedMaritime Port Operations -- Drug-Target Interaction Network Predictions for Drug Repurposing Using LASSO-based Regularized Linear Classification Model -- Optimal Scheduling for Smart Charging of Electric Vehicles Using Dynamic Programming -- Combining MCTS and A3C for Prediction of Spatially Spreading Processes in Forest Wildfire Settings -- Text-based Detection of Unauthorized Users of Social Media Accounts -- N-gram Based Approach for Automatic Prediction of Essay Rubric Marks -- Matching Resumes to Job Descriptions with Stacked Models -- Towards a Comprehensive Evaluation of Recommenders: A Cognition-based Approach -- A Sentence-level Sparse Gamma Topic Model for Sentiment Analysis -- Topic Detection and document Similarity on Financial News -- Software Defect Prediction from Code Quality Measurements via Machine Learning -- Automated Scheduling: Reinforcement Learning Approach to Algorithm Policy Learning -- Estimating Vineyard Grape Yield from Images -- Real-time Deep Learning Pedestrians Classification on a Micro-controller -- A Unified Evaluation Framework for Recommender Systems -- Early Detection of Alzheimer's Disease Using Deep Learning -- Learning with Prior Domain Knowledge and Insufficient Annotated Data -- Predicting Crime Using Spatial Features -- A Tool for Defining and Simulating Storage Strategies on the Smart Grid -- Decision Assist for Self-Driving Cars -- Rule Mining and Prediction Using the Flek Machine -- A New Machine Learning Engine.

This book constitutes the refereed proceedings of the 31th Canadian Conference on Artificial Intelligence, Canadian AI 2018, held in Toronto, ON, Canada, in May 2018. The 16 regular papers and 18 short papers presented together with 7 Graduate Student Symposium papers and 4 Industry Track papers were carefully reviewed and selected from 72 submissions. The focus of the conference was on artificial intelligence research and advanced information and communications technology.