This volume contains 8 lecture notes of the 16th Reasoning Web Summer School (RW 2020), held in Oslo, Norway, in June 2020. The Reasoning Web series of annual summer schools has become the prime educational event in the field of reasoning techniques on the Web, attracting both young and established researchers. The broad theme of this year's summer school was “Declarative Artificial Intelligence” and it covered various aspects of ontological reasoning and related issues that are of particular interest to Semantic Web and Linked Data applications. The following eight lectures have been presented during the school: Introduction to Probabilistic Ontologies, On the Complexity of Learning Description Logic Ontologies, Explanation via Machine Arguing, Stream Reasoning: From Theory to Practice, First-Order Rewritability of Temporal Ontology-Mediated Queries, An Introduction to Answer Set Programming and Some of Its Extensions, Declarative Data Analysis using Limit Datalog Programs, and Knowledge Graphs: Research Directions.

The purpose of the Reasoning Web Summer School is to disseminate recent advances on reasoning techniques and related issues that are of particular interest to Semantic Web and Linked Data applications. It is primarily intended for postgraduate students, postdocs, young researchers, and senior researchers wishing to deepen their knowledge. As in the previous years, lectures in the summer school were given by a distinguished group of expert lecturers. The broad theme of this year's summer school was again “Declarative Artificial Intelligence” and it covered various aspects of ontological reasoning and related issues that are of particular interest to Semantic Web and Linked Data applications. The following eight lectures were presented during the school: Foundations of Graph Path Query Languages; On Combining Ontologies and Rules; Modelling Symbolic Knowledge Using Neural Representations; Mining the Semantic Web with Machine Learning: Main Issues That Need to Be Known; Temporal ASP: From Logical Foundations to Practical Use with telingo; A Review of SHACL: From Data Validation to Schema Reasoning for RDF Graphs; and Score-Based Explanations in Data Management and Machine Learning.

The purpose of the Reasoning Web Summer School is to disseminate recent advances on reasoning techniques and related issues that are of particular interest to Semantic Web and Linked Data applications. It is primarily intended for postgraduate students, postdocs, young researchers, and senior researchers wishing to deepen their knowledge. As in the previous years, lectures in the summer school were given by a distinguished group of expert lecturers. The broad theme of this year's summer school was “Reasoning in Probabilistic Models and Machine Learning” and it covered various aspects of ontological reasoning and related issues that are of particular interest to Semantic Web and Linked Data applications. The following eight lectures were presented during the school: Logic-Based Explainability in Machine Learning; Causal Explanations and Fairness in Data; Statistical Relational Extensions of Answer Set Programming; Vadalog: Its Extensions and Business Applications; Cross-Modal Knowledge Discovery, Inference, and Challenges; Reasoning with Tractable Probabilistic Circuits; From Statistical Relational to Neural Symbolic Artificial Intelligence; Building Intelligent Data Apps in Rel using Reasoning and Probabilistic Modelling.

This book constitutes the proceedings of the Third International Conference, AILA 2023, held in Changchun, China, during August 5–6, 2023. The 26 full papers and the 10 short papers included in this volume were carefully reviewed and selected from 56 submissions. This volume aims to provide novel ideas, original research achievements, and practical experiences in a broad range of artificial intelligence logic and applications.

Artificial intelligence (AI) has been much in the news recently, with some commentators expressing concern that AI might eventually replace humans. But many developments in AI are designed to enhance and supplement the performance of humans rather than replace them, and a novel field of study, with new approaches and solutions to the development of AI, has arisen to focus on this aspect of the technology. This book presents the proceedings of HHAI2023, the 2nd International Conference on Hybrid Human-Artificial Intelligence, held from 26-30 June 2023, in Munich, Germany. The HHAI international conference series is focused on the study of artificially intelligent systems that cooperate synergistically, proactively, responsibly and purposefully with humans, amplifying rather than replacing human intelligence, and invites contributions from various fields, including AI, human-computer interaction, the cognitive and social sciences, computer science, philosophy, among others. A total of 78 submissions were received for the main conference track, and most papers were reviewed by at least three reviewers. The overall final acceptance rate was 43%, with 14 contributions accepted as full papers, 14 as working papers, and 6 as extended abstracts. The papers presented here cover topics including interactive hybrid agents; hybrid intelligence for decision support; hybrid intelligence for health; and values such as fairness and trust in hybrid intelligence. We further accepted 17 posters and 4 demos as well as 8 students to the first HHAI doctoral consortium this year. The authors of 4 working papers and 2 doctoral consortium submissions opted for not publishing their submissions to allow a later full submission, resulting in a total of 57 papers included in this proceedings Addressing all aspects of AI systems that assist humans and emphasizing the need for adaptive, collaborative, responsible, interactive, and human-centered artificial intelligence systems which can leverage human strengths and compensate for human weaknesses while considering social, ethical, and legal considerations, the book will be of interest to all those working in the field.

Inhaltsangabe:Abstract: At present, the World Wide Web faces several problems regarding the search for specific in formation, arising, on the one hand, from the vast number of information sources available, and, on the other hand, from their intrinsic heterogeneity. A promising approach for solving the complex problems emerging in this context is the use of information agents in a multi-agent environment, which cooperatively solve advanced information-retrieval problems. An intelligent information agent provides advanced capabilities resorting to some form of logical reasoning, based on ad-hoc-knowledge about the task in question and on background knowledge of the domain, suitably represented in a knowledge base. In this thesis, our interest is in the role which some methods from the field of declarative logic programming can play in the realization of reasoning capabilities for intelligent information agents. We consider the task of updating extended logic programs (ELPs), since, in order to ensure adaptivity, an agent s knowledge base is subject to change. To this end, we develop update agents, which follow a declarative update policy and a reimplemented in the IMPACT agent environment. The proposed update agents adhere to a clear semantics and are able to deal with incomplete or in consistent information in an appropriate way. Furthermore, we introduce a framework for reasoning about evolving knowledgebases, which are represented as ELPs and maintained by an update policy. We describe a formal model which captures various update approaches, and define a logical language for expressing properties of evolving knowledge bases. We further investigate these mantical properties of knowledge states with respect to reasoning. In particular, we describe finitary characterizations of the knowledge evolution, and derive complexity results for our framework. Finally, we consider aparticular problem of information agents, namely information source selection, and develop an intelligent site-selection agent. We use ELPs for representing relevant knowledge and for declarative query an alysis and query abstraction. We define syntax and semantics of declarative site-selection programs, making use of advanced methods from answer set programming for priority handling and quantitative reasoning. A site selection component is implemented on top of the DLVKR system and its plp front-end for prioritized ELPs. We report experimental results for this implementation, [...]

This book constitutes the refereed proceedings of the 24th International Conference on Practical Aspects of Declarative Languages, PADL 2022, held in Philadelphia, PA, USA, during January 17-18, 2022. The 9 full papers and 4 short papers included in this book were carefully reviewed and selected from 22 submissions. They were organized in topical sections as follows: answer set programming; functional programming; languages, methods and tools; and declarative solutions.

This book contains a collection of revised tutorial papers based on lectures given by researchers at the 5th International Summer School on the Reasoning Web. It introduces semantic web methods and research issues with a particular emphasis on reasoning.

This volume contains 8 lecture notes of the 16th Reasoning Web Summer School (RW 2020), held in Oslo, Norway, in June 2020. The Reasoning Web series of annual summer schools has become the prime educational event in the field of reasoning techniques on the Web, attracting both young and established researchers. The broad theme of this year's summer school was “Declarative Artificial Intelligence” and it covered various aspects of ontological reasoning and related issues that are of particular interest to Semantic Web and Linked Data applications. The following eight lectures have been presented during the school: Introduction to Probabilistic Ontologies, On the Complexity of Learning Description Logic Ontologies, Explanation via Machine Arguing, Stream Reasoning: From Theory to Practice, First-Order Rewritability of Temporal Ontology-Mediated Queries, An Introduction to Answer Set Programming and Some of Its Extensions, Declarative Data Analysis using Limit Datalog Programs, and Knowledge Graphs: Research Directions.

This book presents thoroughly arranged tutorial papers corresponding to lectures given by leading researchers at the Second International Summer School on Reasoning Web in Lisbon, Portugal, in September 2006. Building on the predessor school held in 2005 and published as LNCS 3564, the ten tutorial lectures presented provide competent coverage of current topics in semantic Web research and development.