Автор: Torra Vicenз, Narukawa Yasuo, Nin Jordi Название: Modeling Decisions for Artificial Intelligence: 17th International Conference, Mdai 2020, Sant Cugat, Spain, September 2-4, 2020, Proceedings ISBN: 3030575233 ISBN-13(EAN): 9783030575236 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the 17th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2020, held in Sant Cugat, Spain, in September 2020.*The 24 papers presented in this volume were carefully reviewed and selected from 46 submissions.
Two Algorithms for Additive and Fair Division of Mixed Manna.- Dynamic Play via Suit Factorization Search in Skat.- Dynamic Channel and Layer Gating in Convolutional Neural Network.- Contour-based Segmentation of Historical Printings.- Hybrid Ranking and Regression for Algorithm Selection.- Conditional Reasoning and Relevance.- HTN Plan Repair via Model Transformation.- Nonmonotonic Inferences with Qualitative Conditionals Based on Preferred Structures on Worlds.- Positive Free Higher-Order Logic and its Automation via a Semantical Embedding.- Low-Rank Subspace Override for Unsupervised Domain Adaptation.- Expressive Explanations of DNNs by Combining Concept Analysis with ILP.- Stable Resolving - A Randomized Local Search Heuristic for MaxSAT.- A Virtual Caregiver for Assisted Daily Living of Pre-Frail Users.- Exploring the Effects of Role Design on Agent Learning.- Descriptor Revision for Conditionals: Literal Descriptors and Conditional Preservation.- Multi-Agent Path Finding Modulo Theory with Continuous Movements and the Sum of Costs Objective.- Meta-Induction, Probability Aggregation, and Optimal Scoring.- Cones, Negation, and All That.- Swarm-based Cluster Analysis for Knowledge Discovery.- Draw with Me: Human-in-the-Loop for Image Restoration.- Reasonable Machines: A Research Manifesto.- A Heuristic Agent in Multi-Agent Path Finding Under Destination Uncertainty.- Earnings Prediction with Deep Leaning.- Integrating Keywords into BERT4Rec for Sequential Recommendation.- Modelling and Reasoning in Biomedical Applications with Qualitative Conditional Logic.- Conformal Rule-Based Multi-label Classification.- Optimizing Constraint Satisfaction Problems by Regularization for the Sample Case of the Warehouse Location Problem.- Fast Pathfinding in Knowledge Graphs Using Word Embeddings.- A Visually Explainable Learning System for Skin Lesion Detection Using Multiscale Input with Attention U-Net.- Evaluation of Deep Learning Accelerators for Object Detection at the Edge.-Learning Choice Functions via Pareto-Embeddings.- Simulation-Based Validation of Robot Commands for Force-based Robot Motions.- Firefighter Virtual Reality Simulation for Personalized Stress Detection.- The AI Domain Definition Language (AIDDL) for Integrated Systems.
Автор: Faber Wolfgang, Friedrich Gerhard, Gebser Martin Название: Logics in Artificial Intelligence: 17th European Conference, Jelia 2021, Virtual Event, May 17-20, 2021, Proceedings ISBN: 3030757749 ISBN-13(EAN): 9783030757748 Издательство: Springer Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the proceedings of the 17th European Conference on Logics in Artificial Intelligence, JELIA 2021, held as a virtual event, in May 2021. The accepted papers span a number of areas within Logics in AI, including: argumentation;
Автор: Marreiros Goreti, Melo Francisco S., Lau Nuno Название: Progress in Artificial Intelligence: 20th Epia Conference on Artificial Intelligence, Epia 2021, Virtual Event, September 7-9, 2021, Proceedings ISBN: 3030862291 ISBN-13(EAN): 9783030862299 Издательство: Springer Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the 20th EPIA Conference on Artificial Intelligence, EPIA 2021, held virtually in September 2021.The 62 full papers and 6 short papers presented were carefully reviewed and selected from a total of 108 submissions.
Автор: Goertzel Ben, Panov Aleksandr I., Potapov Alexey Название: Artificial General Intelligence: 13th International Conference, Agi 2020, St. Petersburg, Russia, September 16-19, 2020, Proceedings ISBN: 3030521516 ISBN-13(EAN): 9783030521516 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the 13th International Conference on Artificial General Intelligence, AGI 2020, held in St. Petersburg, Russia, in September 2020.The 30 full papers and 8 short papers presented in this book were carefully reviewed and selected from 60 submissions.
Full Papers.- RepairNet: Contextual Sequence-to-Sequence network for automated program repair.- Seven-year longitudinal implications of wheel spinning and productive persistence.- A Systematic Review of Data-driven Approaches to Item Difficulty Prediction.- Annotating Student Engagement Across Grades 1-12: Associations with Demographics and Expressivity.- Affect-Targeted Interviews for Understanding Student Frustration.- Explainable Recommendations in a Personalized Programming Practice System.- Mutilingual Age of Exposure.- DiSCS: A New Sequence Segmentation Method for Open-Ended Learning Environments.- Interpretable Clustering of Students' Solutions in Introductory Programming.- Adaptively Scaffolding Cognitive Engagement with Batch Constrained Deep Q-Networks.- Ordering Effects in a Role-Based Scaffolding Intervention for Asynchronous Online Discussions.- Option Tracing: Beyond Correctness Analysis in Knowledge Tracing.- An approach for detecting student perceptions of the programming experience from interaction log data.- Discovering Co-creative Dialogue States during Collaborative Learning.- Affective Teacher Tools: Affective Class Report Card and Dashboard.- Engendering Trust in Automated Feedback: A Two Step Comparison of Feedbacks in Gesture Based Learning.- Investigating students' reasoning in a code-tracing tutor.- Evaluating Critical Reinforcement Learning Framework In the Field.- Machine learning models and their development process as learning affordances for humans.- Predicting Co-Occurring Emotions from Eye-Tracking and Interaction Data in MetaTutor.- A Fairness Evaluation of Automated Methods for Scoring Text Evidence Usage in Writing.- The Challenge of Noisy Classrooms: Speaker Detection During Elementary Students' Collaborative Dialogue.- Extracting and Clustering Main Ideas from Student Feedback using Language Models.- Multidimensional Team Communication Modeling for Adaptive Team Training: A Hybrid Deep Learning and Graphical Modeling Framework.- A Good Start is Half the Battle Won: Unsupervised Pre-Training for Low Resource Children's Speech Recognition for an Interactive Reading Companion.- Predicting Knowledge Gain during Web Search based on Multimedia Resource Consumption.- Deep Performance Factors Analysis for Knowledge Tracing.- Gaming and confrustion explain learning advantages for a math digital learning game.- Tackling the Credit Assignment Problem in Reinforcement Learning-Induced Pedagogical Policies with Neural Networks.- TARTA: Teacher Activity Recognizer from Transcriptions and Audio.- Assessing Algorithmic Fairness in Automatic Classifiers of Educational Forum Posts.- "Can you clarify what you said?" Studying the impact of tutee agents' follow-up questions on tutors' learning.- Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT.- A Multidimensional Item Response Theory Model for Rubric-based Writing Assessment.- Towards Bloom's Taxonomy Classification Without Labels.- Automatic Task Requirements Writing Evaluation With Feedback via Machine Reading Comprehension.- Temporal Processes Associating with Procrastination Dynamics.- Investigating Students' Experiences with Collaboration Analytics for Remote Group Meetings.- "Now, I Want to Teach it for Real!" Introducing Machine Learning as a Scientific Discovery Tool for K-12 Teachers, . Better Model, Worse Predictions: The Dangers in Student Model Comparisons.
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