Agents and Artificial Intelligence

13th International Conference, ICAART 2021, Virtual Event, February 4¿6, 2021, Revised Selected Papers
Herausgegeben:Rocha, Ana Paula; Steels, Luc; van den Herik, Jaap

• Broschiertes Buch

Produktbeschreibung

This book constitutes selected papers from the refereed proceedings of the 13th International Conference on Agents and Artificial Intelligence, ICAART 2021, which was held online during February 4-6, 2021.
A total of 72 full and 99 short papers were carefully reviewed and selected for the conference from a total of 298 submissions; 17 selected full papers are included in this book. They were organized in topical sections named agents and artificial intelligence.

Produktdetails

• Lecture Notes in Computer Science 13251
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-10160-1
• 1st ed. 2022
• Seitenzahl: 360
• Erscheinungstermin: 20. Juli 2022
• Englisch
• Abmessung: 235mm x 155mm x 20mm
• Gewicht: 546g
• ISBN-13: 9783031101601
• ISBN-10: 303110160X
• Artikelnr.: 64122432

Inhaltsangabe

Agents.- Specification Aware Multi-Agent Reinforcement Learning.- Task Bundle Delegation for Reducing the Flowtime.- A Detailed Analysis of a Systematic Review about Requirements Engineering Processes for Multi-Agent Systems.- Automatically-generated Agent Organizations for Flexible Work ow Enactment.- Negotiation Considering Privacy Loss on Asymmetric Multi-objective Decentralized Constraint Optimization Problem.- Artificial Intelligence.- Utilizing Out-domain Datasets to Enhance Multi-task Citation Analysis.- Using Possibilistic Networks to Compute Learning Course Indicators.- Assured Deep Multi-Agent Reinforcement Learning for Safe Robotic Systems.- How to Segment Handwritten Historical Chronicles using Fully Convolutional Networks?.- On the Relationship with Toulmin Method to Logic-based Argumentation.- Informer: An e cient Transformer Architecture using Convolutional Layers.- Improving the Generalization of Deep Learning Classification Models in Medical Imaging using Transfer Learning and Generative Adversarial Networks.- An Interpretable Word Sense Classifier for Human Explainable Chatbot.- A Tsetlin Machine Framework for Universal Outlier and Novelty Detection.- Adding Supply/Demand Imbalance-sensitivity to Simple Automated Trader-agents.- Advances in Measuring In ation within Virtual Economies using Deep Reinforcement Learning.- Practical City Scale Stochastic Path Planning with Pre-computation.