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Artificial Intelligence and Machine Learning: 32nd Benelux Conference, BNAIC/Benelearn 2020, Leiden, The Netherlands, November 19–20, 2020, Revised Selected Papers de Mitra Baratchi

Artificial Intelligence and Machine Learning: 32nd Benelux Conference, BNAIC/Benelearn 2020, Leiden, The Netherlands, November 19–20, 2020, Revised Selected Papers: Communications in Computer and Information Science, cartea 1398

Editat de Mitra Baratchi, Lu Cao, Walter A. Kosters, Jefrey Lijffijt, Jan N. van Rijn, Frank W. Takes
en Limba Engleză Paperback – 20 mai 2021
This book contains a selection of the best papers of the 32nd Benelux Conference on Artificial Intelligence, BNAIC/Benelearn 2020, held in Leiden, The Netherlands, in November 2020. Due to the COVID-19 pandemic the conference was held online. 

The 12 papers presented in this volume were carefully reviewed and selected from 41 regular submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.

The chapter 11 is published open access under a CC BY license (Creative Commons Attribution 4.0 International License) 

Chapter “Gaining Insight into Determinants of Physical Activity Using Bayesian Network Learning” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.. 
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Specificații

ISBN-13: 9783030766399
ISBN-10: 303076639X
Pagini: 203
Ilustrații: X, 203 p. 73 illus., 51 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.31 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Cham, Switzerland

Cuprins

Evaluating the Robustness of Question-Answering Models to Paraphrased Questions.- FlipOut: Uncovering Redundant Weights via Sign Flipping.- Evolving Virtual Embodied Agents using External Artifact Evaluations.- Continuous Surrogate-based Optimization Algorithms are Well-suited
for Expensive Discrete Problems.- Comparing Correction Methods to Reduce Misclassification Bias.- A Spiking Neuron Implementation of Genetic Algorithms for Optimization.- Solving Hofstadter's Analogies using Structural Information Theory.- A Semantic Tableau Method for Argument Construction.- `Thy algorithm shalt not bear false witness': An Evaluation of Multiclass Debiasing Methods on Word Embeddings.- An Intelligent Tree Planning Approach using Location-based Social Networks Data.- Gaining Insight into Determinants of Physical Activity using Bayesian Network Learning.- Swarm Construction Coordinated through the Building Material.

Textul de pe ultima copertă

Chapter “Gaining Insight into Determinants of Physical Activity Using Bayesian Network Learning” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.