This book formalizes commonsense knowledge to enable artificial intelligence to understand and engage with the mental lives of people.

This volume is a collection of original contributions about the core knowledge in fundamental domains. It includes work on naive physics, such as formal specifications of intuitive theories of spatial relations, time causality, substance and physical objects, and on naive psychology.

Ontology began life in ancient times as a fundamental part of philosophical enquiry concerned with the analysis and categorisation of what exists. In recent years, the subject has taken a practical turn with the advent of complex computerised information systems which are reliant on robust and coherent representations of their subject matter. The systematisation and elaboration of such representations and their associated reasoning techniques constitute the modern discipline of formal ontology, which is now being applied to such diverse domains as artificial intelligence, computational linguistics, bioinformatics, GIS, knowledge engineering, information retrieval and the Semantic Web. Researchers in all these areas are becoming increasingly aware of the need for serious engagement with ontology, understood as a general theory of the types of entities and relations making up their respective domains of enquiry, to provide a solid foundation for their work. The conference series Formal Ontology in Information Systems (FOIS) provides a meeting point for researchers from these and other disciplines with an interest in formal ontology, where both theoretical issues and concrete applications can be explored in a spirit of genuine interdisciplinarity. This volume contains the proceedings of the sixth FOIS conference, held in Toronto, Canada, during 11-14 May 2010, including invited talks by Francis Jeffry Pelletier, John Bateman, and Alan Rector and the 28 peer-reviewed submissions selected for presentation at the conference, ranging from foundational issues to more application-oriented topics. IOS Press is an international science, technical and medical publisher of high-quality books for academics, scientists, and professionals in all fields. Some of the areas we publish in: -Biomedicine -Oncology -Artificial intelligence -Databases and information systems -Maritime engineering -Nanotechnology -Geoengineering -All aspects of physics -E-governance -E-commerce -The knowledge economy -Urban studies -Arms control -Understanding and responding to terrorism -Medical informatics -Computer Sciences

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How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise. It’s sometime in the not-so-distant future, and you send your fully autonomous self-driving car to the store to pick up your grocery order. The car is endowed with as much capability as an artificial intelligence agent can have, programmed to drive better than you do. But when the car encounters a traffic light stuck on red, it just sits there—indefinitely. Its obstacle-avoidance, lane-following, and route-calculation capacities are all irrelevant; it fails to act because it lacks the common sense of a human driver, who would quickly figure out what’s happening and find a workaround. In Machines like Us, Ron Brachman and Hector Levesque—both leading experts in AI—consider what it would take to create machines with common sense rather than just the specialized expertise of today’s AI systems. Using the stuck traffic light and other relatable examples, Brachman and Levesque offer an accessible account of how common sense might be built into a machine. They analyze common sense in humans, explain how AI over the years has focused mainly on expertise, and suggest ways to endow an AI system with both common sense and effective reasoning. Finally, they consider the critical issue of how we can trust an autonomous machine to make decisions, identifying two fundamental requirements for trustworthy autonomous AI systems: having reasons for doing what they do, and being able to accept advice. Both in the end are dependent on having common sense.

Now in paperback for the first time since its original publication, the material gathered here is perfect for anyone who needs a detailed and accessible introduction to the important semantic theories. Designed for a wide audience, it will be of great value to linguists, cognitive scientists, philosophers, and computer scientists working on natural language. The book covers theories of lexical semantics, cognitively oriented approaches to semantics, compositional theories of sentence semantics, and discourse semantics. This clear, elegant explanation of the key theories in semantics research is essential reading for anyone working in the area.

This book constitutes the proceedings of the 41st SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2021, which was supposed to be held in Cambridge, UK, in December 2021. The conference was held virtually due to the COVID-19 pandemic. The 22 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 37 submissions. The volume includes technical papers presenting new and innovative developments in the field as well as application papers presenting innovative applications of AI techniques in a number of subject domains. The papers are organized in the following topical sections: technical paper; machine learning; AI techniques; short technical stream papers; application papers; applications of machine learning; AI for medicine; advances in applied AI; and short application stream papers.

If only it were possible to develop automated and trainable neural systems that could justify their behavior in a way that could be interpreted by humans like a symbolic system. The field of Neurosymbolic AI aims to combine two disparate approaches to AI; symbolic reasoning and neural or connectionist approaches such as Deep Learning. The quest to unite these two types of AI has led to the development of many innovative techniques which extend the boundaries of both disciplines. This book, Compendium of Neurosymbolic Artificial Intelligence, presents 30 invited papers which explore various approaches to defining and developing a successful system to combine these two methods. Each strategy has clear advantages and disadvantages, with the aim of most being to find some useful middle ground between the rigid transparency of symbolic systems and the more flexible yet highly opaque neural applications. The papers are organized by theme, with the first four being overviews or surveys of the field. These are followed by papers covering neurosymbolic reasoning; neurosymbolic architectures; various aspects of Deep Learning; and finally two chapters on natural language processing. All papers were reviewed internally before publication. The book is intended to follow and extend the work of the previous book, Neuro-symbolic artificial intelligence: The state of the art (IOS Press; 2021) which laid out the breadth of the field at that time. Neurosymbolic AI is a young field which is still being actively defined and explored, and this book will be of interest to those working in AI research and development.

This book constitutes the refereed proceedings of the 16th International Conference on Artificial General Intelligence, AGI 2023, held in Stockholm, Sweden in June 2023. The 35 full papers and one short paper presented in this book were carefully reviewed and selected from 72 submissions. The papers cover topics from foundations of AGI, to AGI approaches and AGI ethics, to the roles of systems biology, goal generation, and learning systems, and so much more.

This book constitutes the refereed proceedings of the 12th International Conference on Intelligent Virtual Agents, IVA 2012, held in Santa Cruz, CA, USA, in September 2012. The 17 revised full papers presented together with 31 short papers and 18 poster papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on IVAs on learning environments; emotion and personality; evaluation and empirical studies; multimodal perception and expression; narrative and interactive applications; social interaction; authoring and tools; conceptual frameworks.