Bramer / Petridis Artificial Intelligence XXXIV

37th SGAI International Conference on Artificial Intelligence, AI 2017, Cambridge, UK, December 12-14, 2017, Proceedings
1. Auflage 2017
ISBN: 978-3-319-71078-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 10630, 430 Seiten, eBook

Reihe: Lecture Notes in Computer Science

This book constitutes the proceedings of the 37th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2017, held in Cambridge, UK, in December 2017. The 25 full papers and 12 short papers presented in this volume were carefully reviewed and selected from 55 submissions. There are technical and application papers which were organized in topical sections named: machine learning and neural networks; machine learning, speech and vision and fuzzy logic; short technical papers; AI for healthcare; applications of machine learning; applications of neural networks and fuzzy logic; case-based reasoning; AI techniques; and short applications papers.

Zielgruppe

Research

Autoren/Hrsg.

Bramer, Max

Petridis, Miltos

Inhaltsverzeichnis

TECHNICAL STREAM PAPERS.- BEST TECHNICAL PAPER .- Using Constraint Satisfaction Problem Solving to Enable Workflow Flexibility by Deviation.- MACHINE LEARNING AND NEURAL NETWORKS.- Masked Conditional Neural Networks for Environmental Sound Classification.- Ensembles of Recurrent Neural Networks for Robust Time Series Forecasting.- A Blackboard based Hybrid Multi-Agent System for Improving Classification Accuracy using Reinforcement Learning Techniques.- MACHINE LEARNING, SPEECH AND VISION AND FUZZY LOGIC.- Programming Without Program or How To Program in Natural Language Utterances.- Capturing the Dynamics of Cellular Automata, for the Generation of Synthetic Persian Music, Using Conditional Restricted Boltzmann Machines.- Measuring Relations between Concepts in Conceptual Spaces.- Towards a Deep reinforcement learning approach for Tower Line Wars.- Improving Modular Classification Rule Induction with G-Prism using Dynamic Rule Term Boundaries.- SHORT TECHNICAL PAPERS.- Inference and discovery in remote sensing data with features extracted using deep networks.- Quantization Error-based Regularization in Neural Networks.- Knowledge Transfer in Neural Language Models.- Emotion Recognition in Text Using PPM.- An experimental comparison of ensemble classifiers for evolving data streams.- A learning automata Local Contribution Sampling applied to hydropower production optimization.- Toward Component Based Self-Adaptive Multi-Strategic Pedagogical Agent.- APPLICATION STREAM PAPERS.- BEST APPLICATION PAPER.- Cable Belief Networks.- AI FOR HEALTHCARE.- Towards the Integration of Prescription Analytics into Health Policy and General Practice.- An Ontology to support Knowledge Management in Behaviour-based Healthcare.- Using Semantic Web technologies to underpin the SNOMED CT query language.- APPLICATIONS OF MACHINE LEARNING.- Feature Level Ensemble Method for Classifying Multi-media Data.- Reliability Based Bayesian Inference for Probabilistic Classification: An Overview ofSampling Schemes.- Algorithms and Architecture for Real-time Recommendations at News UK.- Customer Contact Journey Prediction.- APPLICATIONS OF NEURAL NETWORKS AND FUZZY LOGIC.- A Better Predictor of Marathon Race Times based on Neural Networks.- Fuzzy Logic Based Personalized Task Recommendation System for Field Services.- Application of Neural Network in Modeling Commuter Choice Behavior with a Novel Fuzzy Access Measure.- CASE-BASED REASONING.- Predicting Fraud in Mobile Money Transfer Using Case-Based Reasoning.- Predicting Dust Storms Using Hybrid Intelligence System.- AI TECHNIQUES.- Decision support system for green real-life field scheduling problems.- Multi-label Classification of Movie Posters into Genres with Rakel ensemble method.- Parameter Search for a small swarm of AUVs using Particle Swarm Optimisation.- SHORT APPLICATION PAPERS.- Deep learning for classification of bi-lingual ads in online classifieds.- Enhancing Symmetry in GAN Generated Fashion Images.- Predicting Service Levels Using Neural Networks.- Using Machine Learning for Dynamic Multicast Capacity Planning.- Asynchronous Population-Based Hill Climbing Applied to SPICE Model Generation from EM Simulation Data.