Neuro Symbolic Reasoning and Learning
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Neuro symbolic artificial intelligence (NSAI) encompasses the combination of deep neural networks with symbolic logic for reasoning and learning tasks. NSAI frameworks are now capable of embedding prior knowledge in deep learning architectures, guiding the learning process with logical constraints, providing symbolic explainability, and using gradient-based approaches to learn logical statements. Several approaches are seeing usage in various application areas.
This book is designed for researchers and advanced-level students trying to understand the current landscape of NSAI research as well as those looking to apply NSAI research in areas such as natural language processing and visual question answering. Practitioners who specialize in employing machine learning and AI systems for operational use will find this book useful as well.
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Gerardo I. Simari is a professor at UNS, and a researcher at CONICET. His research focuses on AI and Databases, and reasoning under uncertainty. He received a PhD in computer science from University of Maryland College Park and later joined the Department of Computer Science, University of Oxford, where he was also a Fulford Junior Research Fellow of Somerville College.
Chitta Baral is a Professor at the Arizona State University, and a past President of KR Inc. His research interests include Knowledge Representation and Reasoning, NLP and Image Understanding and often involves combining logical reasoning with explicit knowledge and neural learning and reasoning with textual and perceptual inputs.
Bowen Xi is a Ph.D. student at Arizona State University, specializing in the field of Neural Symbolic AI. She is passionate about combining the strengths of neural networks and symbolic reasoning to advance the field of artificial intelligence. Bowen's research interests include developing novel algorithms and techniques that enable machines to learn and reason like humans.
Lahari Pokala is a student pursuing her Master's degree at Arizona State University, where she is majoring in Computer Science. Her interests lie in artificial intelligence and data engineering.
