Applying mechanisms and principles of human intelligence and converging the brain and artificial intelligence (AI) is currently a research trend. The applications of AI in brain simulation are countless. Brain-inspired intelligent systems will improve next-generation information processing by applying theories, techniques, and applications inspired by the information processing principles from the brain. Exploring Future Opportunities of Brain-Inspired Artificial Intelligence focuses on the convergence of AI with brain-inspired intelligence. It presents research on brain-inspired cognitive machines with vision, audition, language processing, and thinking capabilities. Covering topics such as data analysis tools, knowledge representation, and super-resolution, this premier reference source is an essential resource for engineers, developers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

The two volume set LNCS 13258 and 13259 constitutes the proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, held in Puerto de la Cruz, Tenerife, Spain in May – June 2022. The total of 121 contributions was carefully reviewed and selected from 203 submissions. The papers are organized in two volumes, with the following topical sub-headings: Part I: Machine Learning in Neuroscience; Neuromotor and Cognitive Disorders; Affective Analysis; Health Applications Part II: Affective Computing in Ambient Intelligence; Bioinspired Computing Approaches; Machine Learning in Computer Vision and Robot; Deep Learning; Artificial Intelligence Applications.

This book encapsulates and occupies recent advances and state-of-the-art applications of nature-inspired computing (NIC) techniques in the field of bioinformatics and computational biology, which would aid medical sciences in various clinical applications. This edited volume covers fundamental applications, scope, and future perspectives of NIC techniques in bioinformatics including genomic profiling, gene expression data classification, DNA computation, systems and network biology, solving personalized therapy complications, antimicrobial resistance in bacterial pathogens, and computer-aided drug design, discovery, and therapeutics. It also covers the role of NIC techniques in various diseases and disorders, including cancer detection and diagnosis, breast cancer, lung disorder detection, disease biomarkers, and potential therapeutics identifications.

Towards Neuromorphic Machine Intelligence: Spike-Based Representation, Learning, and Applications provides readers with in-depth understanding of Spiking Neural Networks (SNNs), which is a burgeoning research branch of Artificial Neural Networks (ANNs), AI, and Machine Learning that sits at the heart of the integration between Computer Science and Neural Engineering. In recent years, neural networks have re-emerged in relation to AI, representing a well-grounded paradigm rooted in disciplines from physics and psychology to information science and engineering.This book represents one of the established cross-over areas where neurophysiology, cognition, and neural engineering coincide with the development of new Machine Learning and AI paradigms. There are many excellent theoretical achievements in neuron models, learning algorithms, network architecture, and so on. But these achievements are numerous and scattered, with a lack of straightforward systematic integration, making it difficult for researchers to assimilate and apply. As the third generation of Artificial Neural Networks (ANNs), Spiking Neural Networks (SNNs) simulate the neuron dynamics and information transmission in a biological neural system in more detail, which is a cross-product of computer science and neuroscience. The primary target audience of this book is divided into two categories: artificial intelligence researchers who know nothing about SNNs, and researchers who know a lot about SNNs. The former needs to acquire fundamental knowledge of SNNs, but the challenge is that much of the existing literature on SNNs only slightly mentions the basic knowledge of SNNs, or is too superficial, and this book gives a systematic explanation from scratch. The latter needs learning about some novel research achievements in the field of SNNs, and this book introduces the latest research results on different aspects of SNNs and provides detailed simulation processes to facilitate readers' replication. In addition, the book introduces neuromorphic hardware architecture as a further extension of the SNN system.The book starts with the birth and development of SNNs, and then introduces the main research hotspots, including spiking neuron models, learning algorithms, network architectures, and neuromorphic hardware. Therefore, the book provides readers with easy access to both the foundational concepts and recent research findings in SNNs. - Introduces Spiking Neural Networks (SNNs), a new generation of biologically inspired artificial intelligence. - Systematically presents basic concepts of SNNs, neuron and network models, learning algorithms, and neuromorphic hardware. - Introduces the latest research results on various aspects of SNNs and provides detailed simulation processes to facilitate readers' replication.

The two volume set LNCS 13258 and 13259 constitutes the proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, held in Puerto de la Cruz, Tenerife, Spain in May – June 2022. The total of 121 contributions was carefully reviewed and selected from 203 submissions. The papers are organized in two volumes, with the following topical sub-headings: Part I: Machine Learning in Neuroscience; Neuromotor and Cognitive Disorders; Affective Analysis; Health Applications, Part II: Affective Computing in Ambient Intelligence; Bioinspired Computing Approaches; Machine Learning in Computer Vision and Robot; Deep Learning; Artificial Intelligence Applications.

This volume, in conjunction with the two volumes CICS 0002 and LNCS 4681, constitutes the refereed proceedings of the Third International Conference on Intelligent Computing held in Qingdao, China, in August 2007. The 139 full papers published here were carefully reviewed and selected from among 2,875 submissions. These papers offer important findings and insights into the field of intelligent computing.

This book provides a comprehensive account of Chinese AI in its various facets, based on primary Chinese-language sources. China’s rise as an AI power is an event of importance to the world and a potential challenge to liberal democracies. Filling a gap in the literature, this volume is fully documented, data-driven, and presented in a scholarly format suitable for citation and for supporting downstream research, while also remaining accessible to laypersons. It brings together 15 recognized international experts to present a full treatment of Chinese artificial intelligence. The volume contains chapters on state, commercial, and foreign sources of China’s AI power; China’s AI talent, scholarship, and global standing; the impact of AI on China’s development of cutting-edge disciplines; China’s use of AI in military, cyber, and surveillance applications; AI safety, threat mitigation, and the technology’s likely trajectory. The book ends with recommendations drawn from the authors’ interactions with policymakers and specialists worldwide, aimed at encouraging AI’s healthy development in China and preparing the rest of the world to engage with it. This book will be of much interest to students of Chinese politics, science and technology studies, security studies and international relations.

This two-volume set of LNCS 12463 and LNCS 12464 constitutes - in conjunction with the volume LNAI 12465 - the refereed proceedings of the 16th International Conference on Intelligent Computing, ICIC 2020, held in Bari, Italy, in October 2020. The 162 full papers of the three proceedings volumes were carefully reviewed and selected from 457 submissions. The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, addressing theories, methodologies, and applications in science and technology.

Zusammenfassung: The two volume set LNCS 14674 and 14675 constitutes the proceedings of the 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, which took place in Olhâo, Portugal, during June 4-7, 2024. The 99 full papers presented in these proceedings were carefully reviewed and selected from 193 submissions. They were organized in topical sections as follows: Part I: Machine learning in neuroscience; artificial intelligence in neurophysiology; neuromotor and cognitive disorders; intelligent systems for assessment, treatment, and assistance in early stages of Alzheimer's disease and other dementias; socio-cognitive, affective and physiological computing; affective computing and context awareness in ambientintelliigence; learning tools to lecture; Part II: Machine learning in computer vision and robotics; bio-inspired computing approaches; social and civil engineering through human AI translations; smart renewable energies: advancing AI algorithms in the renewable energy industry; bioinspired applications