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Titlebook: Highlights in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Coll; International Worksh Fernando De La P

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發(fā)表于 2025-3-28 17:33:08 | 只看該作者
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發(fā)表于 2025-3-28 20:08:16 | 只看該作者
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發(fā)表于 2025-3-29 02:50:13 | 只看該作者
Conference proceedings 2021-Agent Systems, PAAMS 2021, held in Salamanca, Spain, in October 2021..The total of 17 full and 9 short papers presented in this volume were carefully selected from 42 submissions..The papers in this volume stem from the following meetings:Workshop on Character Computing (C2); Workshop on Deep Learn
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發(fā)表于 2025-3-29 06:40:26 | 只看該作者
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發(fā)表于 2025-3-29 10:41:13 | 只看該作者
A Hybrid Supervised/Unsupervised Machine Learning Approach to Classify Web Servicesmerative hierarchical clustering algorithm. Second, several supervised learning algorithms have been applied to determine service categories. The findings show that the hybrid approach using the combination of hierarchical clustering and SVM provides acceptable results in comparison with other unsupervised/supervised combinations.
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發(fā)表于 2025-3-29 13:01:12 | 只看該作者
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發(fā)表于 2025-3-29 17:07:38 | 只看該作者
XReC: Towards a Generic Module-Based Framework for Explainable Recommendation Based on Charactery after the outbreak of the COVID-19, people head to the virtual world by shopping online instead of going to the actual store, watching movies on platforms like “Netflix” instead of going to cinemas, or companies are applying different methods to continue their internal operations online. So most c
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發(fā)表于 2025-3-29 20:10:26 | 只看該作者
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發(fā)表于 2025-3-30 01:51:29 | 只看該作者
Contributions of Character Computing to AI Based Adaptive Learning Environments – A Discussion which can be exploited for personalized learning using AI based approaches of XAI and active learning. Integrating concepts of character computing enables a more robust adaptation to the learner’s needs. The paper discusses future application scenarios of XAI, virtual learning companions and social
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發(fā)表于 2025-3-30 07:18:18 | 只看該作者
An Attentional Model for Earthquake Prediction Using Seismic Datae; therefore, techniques to predict such events are essential to minimize their impacts. However, despite all efforts to estimate the occurrence of a disaster, making an accurate and robust forecast is a challenging task. In recent years, Deep Learning techniques have innovated several fields by lea
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