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This book constitutes the proceedings of the Third International Workshop on Explainable, Transparent AI and Multi-Agent Systems, EXTRAAMAS 2021, which was held virtually due to the COVID-19 pandemic. The 19 long revised papers and 1 short contribution were carefully selected from 32 submissions. The papers are organized in the following topical sections: XAI & machine learning; XAI vision, understanding, deployment and evaluation; XAI applications; XAI logic and argumentation; decentralized and heterogeneous XAI.
This book constitutes the proceedings of the First International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, EXTRAAMAS 2019, held in Montreal, Canada, in May 2019. The 12 revised and extended papers presented were carefully selected from 23 submissions. They are organized in topical sections on explanation and transparency; explainable robots; opening the black box; explainable agent simulations; planning and argumentation; explainable AI and cognitive science.
Human and organizational factors have a substantial impact on the performance of planning and scheduling processes. Despite widespread and advanced decision support systems, human decision makers are still crucial to improve the operational performance in manufacturing industries. In this text, the state of the art in this area is discussed by experts from a wide variety of engineering and social science disciplines. Moreover, recent results from collaborative studies and a number of field cases are presented. The text is targeted at researchers and graduate students, but is also particularly useful for managers, consultants, and system developers to better understand how human performance can be advanced.
"Abstract: Supply chain management contends with structures and processes for delivering goods and services to customers. It addresses the core functions of connected businesses to meet downstream demand. This innovative volume provides an authoritative and timely guide to the overarching issues that are ubiquitous throughout the supply chain. In particular, it addresses emerging issues that are applicable across supply chains-such as data science, financial flows, human capital, internet technologies, risk management, cyber security, and supply networks. With chapters from an international roster of leading scholars in the field, The Oxford Handbook of Supply Chain Management is a necessary resource for all students and researchers of the field as well as for forward-thinking practitioners. Keywords: supply chain management; value; human society; goods and services; competitive advantage; people and welfare; data and technology; moving goods and services; structure and strategy; growing and sustaining"--
This book constitutes the proceedings of the 19th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2021, held in Salamanca, Spain, in October 2021. The 27 regular and 13 short papers presented in this volume were carefully reviewed and selected from 56 submissions. They deal with the application and validation of agent-based models, methods, and technologies in a number of key applications areas, including: advanced models and learning, agent-based programming, decision-making, education and social interactions, formal and theoretic models, health and safety, mobility and the city, swarms and task allocation.
This three-volume set constitutes the refereed proceedings of the First World Conference on Explainable Artificial Intelligence, xAI 2023, held in Lisbon, Portugal, in July 2023. The 94 papers presented were thoroughly reviewed and selected from the 220 qualified submissions. They are organized in the following topical sections: Part I: Interdisciplinary perspectives, approaches and strategies for xAI; Model-agnostic explanations, methods and techniques for xAI, Causality and Explainable AI; Explainable AI in Finance, cybersecurity, health-care and biomedicine. Part II: Surveys, benchmarks, visual representations and applications for xAI; xAI for decision-making and human-AI collaboration, for Machine Learning on Graphs with Ontologies and Graph Neural Networks; Actionable eXplainable AI, Semantics and explainability, and Explanations for Advice-Giving Systems. Part III: xAI for time series and Natural Language Processing; Human-centered explanations and xAI for Trustworthy and Responsible AI; Explainable and Interpretable AI with Argumentation, Representational Learning and concept extraction for xAI.
The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models;...
This book aims to explore how to automate, innovate, design, and deploy emerging technologies in actuarial work transformations for the insurance and finance sector. It examines the role of artificial intelligence with process automation in daily monitoring of solvency, governance, compliance, data processes, etc. It also explores the usage of machine learning, telematics system, AI-enabled claim processing software, Big Data and Algorithms, Explainable AI, and AI-enabled risk management tools in various actuarial processes. This book: • Presents case studies and best practices with real-world examples of successful and unsuccessful actuarial work transformation initiatives and transformat...
This book constitutes the refereed post proceedings of the XIXth International Conference of the Italian Association for Artificial Intelligence, AIxIA 2020, held in Milano, Italy, in November 2020.Due to the COVID-19 pandemic, the conference was "rebooted"/ re-organized w.r.t. the original format. The 27 full papers were carefully reviewed and selected from 89 submissions. The society aims at increasing the public awareness of Artificial Intelligence, encouraging the teaching and promoting research in the field.