Tag: machine-learning
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Agents and Artificial Intelligence | 13 Volumes
Agents and Artificial Intelligence is an extensive compendium that encapsulates over a decade of pioneering research and philosophical inquiry into the realms of artificial intelligence and agent-based systems. Spanning 13 volumes derived from the International Conference on Agents and Artificial Intelligence (ICAART) held annually from 2009 to 2021, this collection represents a curation of the…
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Hybrid Artificial Intelligent Systems | 6 Volumes
Hybrid Artificial Intelligent Systems is a comprehensive anthology spanning six volumes, encapsulating the proceedings of the 13th to the 18th International Conferences on Hybrid Artificial Intelligent Systems (HAIS) held in Spain from 2018 to 2023. Edited by a distinguished group of scholars including Hilde Pérez García, Lidia Sánchez González, Manuel Castejón Limas, Héctor Quintián, Emilio…
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Explainable and Transparent AI and Multi-Agent Systems | 3 Volumes
The anthology Explainable and Transparent AI and Multi-Agent Systems is a monumental compilation that encapsulates the forefront of research and philosophical inquiry into the realms of explainable artificial intelligence (XAI) and multi-agent systems (MAS). Spanning three significant international workshops—EXTRAAMAS 2021, held virtually due to the global pandemic; EXTRAAMAS 2022, also conducted virtually; and EXTRAAMAS 2023…
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Explainable Artificial Intelligence: First World Conference, xAI 2023 | 3 Volumes
Explainable Artificial Intelligence: First World Conference, xAI 2023, edited by Luca Longo, represents a monumental compilation of cutting-edge research that goes into the burgeoning field of explainable artificial intelligence (XAI). This three-volume set emerges from the proceedings of the inaugural xAI 2023 conference held in Lisbon, Portugal, and encompasses a comprehensive spectrum of 94 rigorously…
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xxAI – Beyond Explainable AI
xxAI – Beyond Explainable AI represents a significant milestone in the ongoing mission to bridge the gap between complex machine learning models and human interpretability. Edited by Andreas Holzinger, Randy Goebel, Ruth Fong, Taesup Moon, Klaus-Robert Müller, and Wojciech Samek, this volume encapsulates the forefront of research in explainable artificial intelligence (xAI), extending its boundaries…
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Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning
Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning by Uday Kamath and John Liu is a seminal work in the evolving landscape of artificial intelligence, particularly in the critical domain of explainable AI (XAI). As AI systems become increasingly integrated into the fabric of society, influencing decisions in healthcare, finance, justice, and beyond, the…
Simon Gros 