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Hybrid Intelligent Systems
This book presents 48 selected papers focused on Large Language Models and Machine Learning from the 23rd International Conference on Hybrid Intelligent Systems, which was held in five different cities namely Olten, Switzerland; Porto, Portugal; Kaunas, Lithuania; Greater Noida, India; Kochi, India and in online mode. The 23rd International Conference on Hybrid Intelligent Systems (HIS 2023) was focusing on synergistic combinations of multiple approaches to develop the next generation of intelligent systems. HIS 2023 had contributions by authors from 44 countries. This book offers a valuable reference guide for all scientists, academicians, researchers, students, and practitioners in the field of artificial intelligence and deep learning.
R 8,059.00
9th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA’25), Volume 2
This volume explores the forefront of AI innovation in building secure, sustainable, and intelligent systems. From adaptive blockchain solutions for IoT and advances in photonic quantum computing to DNS-based cyber defense and disaster-resilient sensor networks, the research presented addresses critical challenges in digital infrastructure. Additional highlights include AI-driven environmental forecasting, assistive technologies for dyslexia, and machine learning applications in law enforcement--demonstrating AI's expanding role in safeguarding infrastructure, optimizing resources, and advancing societal resilience.
R 10,469.28
Probabilistic Reasoning in Intelligent Systems
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
R 2,147.00
Artificial Intelligence: A New Synthesis
Intelligent agents are employed as the central characters in this introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. A distinguishing feature of this text is in its evolutionary approach to the study of AI. This book provides a refreshing and motivating synthesis of the field by one of AI's master expositors and leading researches.
R 2,265.00
Intelligent Systems Modeling and Simulation III
This book continues the previous edition: Samsul Ariffin Abdul Karim (2022). Intelligent Systems Modeling and Simulation II: Machine Learning, Neural Networks, Efficient Numerical Algorithm and Statistical Methods, Studies in Systems, Decision and Control (SSDC, volume 444, 22k Access). After two years, Intelligent Systems Modeling and Simulation have evolved tremendously through the latest and advanced emergence technologies and many highly sophisticated algorithms have been developed by blending artificial intelligence (AI) and mathematics, statistics, data modelling and other related research areas. These blends offer many opportunities and further investigations into the overlapand equality between these areas. It is a well-known fact that most industries and companies have utilized this IR4.0 architecture in various levels of manufacturing and decision processes. Besides, nowadays IR5.0 or Society5.0 has also been embedded into various systems in industries as well as in Teaching and Learning (TL). The combination of IR4.0 and Society 5.0 may result in more impactful outcomes, especially in automated decision-making and reliable simulations-based modelling. Furthermore, IR4.0 and Society5.0 through Data-Driven have made a significant contribution to the government and companies to analyse big data via predictive analytics. Cyber security firewalls on all systems must be up to date to prevent any malicious attacks by hackers. Otherwise, our citizens might be scammed and according to NBC News, the total loss for 2022 is around USD 8.8 billion. These are very huge amount. Just recently, COVID-19 has been spreading all over the world again. To assist the Ministry of Health (MOH) and other government agencies, it is very crucial to identify, predict, detect and quarantine the COVID-19 on the susceptible persons soonest possible. Intelligent Image Processing techniques are very demanding here. This is to ensure that we can control and minimise the spread. Inspire by these latest developments, in this book, various experts in the areas of Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Modeling and Simulation, Cyber Security and Awareness, Intelligent Statistical Methods, Big Data Analytics, Sentiment Analytics, Intelligent Function Approximation, Image Processing in medical imaging especially on COVID-19, AI in Teaching and Learning, and Computational Intelligence will share their latest studies and experiences. Their finding is in line with United Nations Sustainable Development Goals (SDGs) such as No. 9: Industry, Innovation, and Infrastructure, particularly Target 9.4, 9.5, 9.a, 9.b and 9.c, No. 11: Sustainable Cities and Communities particularly Target 11.b and Indicators 11.b.1 and 11.b.2, and SDG No. 4: Quality Education; particularly Target 4.7 and Indicator 4.7.1. This book is highly suitable for postgraduate students and researchers to get the state-of-the-art current research directions as well as for the sci
R 10,798.01
Artificial Intelligence and Machine Learning
This book contains a selection of the best papers of the 32nd Benelux Conference on Artificial Intelligence, BNAIC/Benelearn 2020, held in Leiden, The Netherlands, in November 2020. Due to the COVID-19 pandemic the conference was held online. The 12 papers presented in this volume were carefully reviewed and selected from 41 regular submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.The chapter 11 is published open access under a CC BY license (Creative Commons Attribution 4.0 International License) Chapter “Gaining Insight into Determinants of Physical Activity Using Bayesian Network Learning” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com..
R 1,946.66
Advanced Artificial Intelligence (Third Edition)
This third edition comprehensively captures the cutting-edge research achievements of AI. Topics are thoroughly revised and updated, presenting the latest techniques and strategies to address the impending challenges facing computer scientists today.The useful reference text benefits professionals, academics, researchers, senior and graduate students in the information field and related tertiary specialties.
R 5,422.00
Demystifying Federated Learning for Blockchain and Industrial Internet of Things
In recent years, mobile technology and the internet of objects have been used in mobile networks to meet new technical demands. Emerging needs have centered on data storage, computation, and low latency management in potentially smart cities, transport, smart grids, and a wide number of sustainable environments. Federated learning's contributions include an effective framework to improve network security in heterogeneous industrial internet of things (IIoT) environments. Demystifying Federated Learning for Blockchain and Industrial Internet of Things rediscovers, redefines, and reestablishes the most recent applications of federated learning using blockchain and IIoT to optimize data for next-generation networks. It provides insights to readers in a way of inculcating the theme that shapes the next generation of secure communication. Covering topics such as smart agriculture, object identification, and educational big data, this premier reference source is an essential resource for computer scientists, programmers, government officials, business leaders and managers, students and faculty of higher education, researchers, and academicians.
R 10,406.46
Machine Intelligence, Tools, and Applications
This book presents the recent advances including tools and techniques in the constantly changing landscape of machine learning (ML). This would enable the readers with a strong understanding of critical issues in ML by providing both broad and detailed perspectives on cutting-edge theories, algorithms, and tools. This will become a single source of reference on conceptual, methodological, technical, and managerial issues, as well as provide insight into emerging trends and future opportunities in the discipline of ML. This book contains altogether 36 chapters in the area of ML and its applications.
R 10,560.80
Handbook of Research on AI and ML for Intelligent Machines and Systems
The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. This handbook bridges the gap by presenting a comprehensive understanding of this fusion and its implications for the field. This book delves into the world of intelligent machines, revealing how they interact autonomously with their environment and adapt seamlessly to new situations. By harnessing the power of AI and ML, these smart devices can accomplish complex tasks such as traffic monitoring, speech recognition, face recognition, and automatic manufacturing, significantly enhancing operational efficiency. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.
R 14,672.92
Recent Studies on Computational Intelligence
This book gathers the latest quality research work of Ph.D. students working on the current areas presented in the Doctoral Symposium on Computational Intelligence (DoSCI 2020). The book includes works in the areas of artificial intelligence, deep learning, evolutionary algorithms, swarm intelligence, fuzzy sets and vague sets, rough set theoretic approaches, quantum-inspired computational intelligence, hybrid computational intelligence, machine learning, computer vision, soft computing, distributed computing, parallel and grid computing, cloud computing, high-performance computing, biomedical computing, decision support and decision making. The book is useful for researchers, students, engineers, practitioners and academicians in their advance studies.
R 5,070.49
Recent Studies on Computational Intelligence
This book gathers the latest quality research work of Ph.D. students working on the current areas presented in the Doctoral Symposium on Computational Intelligence (DoSCI 2020). The book includes works in the areas of artificial intelligence, deep learning, evolutionary algorithms, swarm intelligence, fuzzy sets and vague sets, rough set theoretic approaches, quantum-inspired computational intelligence, hybrid computational intelligence, machine learning, computer vision, soft computing, distributed computing, parallel and grid computing, cloud computing, high-performance computing, biomedical computing, decision support and decision making. The book is useful for researchers, students, engineers, practitioners and academicians in their advance studies.
R 4,915.10
Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning
This book is written both for readers entering the field, and for practitioners with a background in AI and an interest in developing real-world applications. The book is a great resource for practitioners and researchers in both industry and academia, and the discussed case studies and associated material can serve as inspiration for a variety of projects and hands-on assignments in a classroom setting. I will certainly keep this book as a personal resource for the courses I teach, and strongly recommend it to my students. --Dr. Carlotta Domeniconi, Associate Professor, Computer Science Department, GMUThis book offers a curriculum for introducing interpretability to machine learning at every stage. The authors provide compelling examples that a core teaching practice like leading interpretive discussions can be taught and learned by teachers and sustained effort. And what better way to strengthen the quality of AI and Machine learning outcomes. I hope that this book will become a primer for teachers, data Science educators, and ML developers, and together we practice the art of interpretive machine learning.--Anusha Dandapani, Chief Data and Analytics Officer, UNICC and Adjunct Faculty, NYUThis is a wonderful book! I’m pleased that the next generation of scientists will finally be able to learn this important topic. This is the first book I’ve seen that has up-to-date and well-rounded coverage. Thank you to the authors!--Dr. Cynthia Rudin, Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, and Biostatistics & Bioinformatics Literature on Explainable AI has up until now been relatively scarce and featured mainly mainstream algorithms like SHAP and LIME. This book has closed this gap by providing an extremely broad review of various algorithms proposed in the scientific circles over the previous 5-10 years. This book is a great guide to anyone who is new to the field of XAI or is already familiar with the field and is willing to expand their knowledge. A comprehensive review of the state-of-the-art Explainable AI methods starting from visualization, interpretable methods, local and global explanations, time series methods, and finishing with deep learning provides an unparalleled source of information currently unavailable anywhere else. Additionally, notebooks with vivid examples are a great supplement that makes the book even more attractive for practitioners of any level.Overall, the authors provide readers with an enormous breadth of coverage without losing sight of practical aspects, which makes this book truly unique and a great addition to the library of any data scientist.Dr. Andrey Sharapov, Product Data Scientist, Explainable AI Expert and Speaker, Founder of Explainable AI-XAI Group
R 4,563.08
Multi-LLM Agent Collaborative Intelligence
Today's large language models excel at pattern recall yet falter on long-range planning, self-critique, context loss, and the tendency of maximum-likelihood training to reward popularity over quality. MACI offers a promising route to AGI by orchestrating specialized LLM agents through explicit protocols rather than enlarging a single model. Several modules remedy complementary weaknesses: adversarial-collaborative debate surfaces hidden assumptions; critical-reading rubrics filter incoherent arguments; information-theoretic signals steer dialogue quantitatively; transactional memory enables reliable long-horizon execution; and a dual-agent ethical court adjudicates outputs. Crucially, MACI also modulates linguistic behavior, tuning each agent's contentiousness and emotional tone, so the collective explores ideas from contrasting, affect-aware perspectives before converging.Fourteen aphorisms distill the framework's philosophy, including "Intelligence emerges from regulated collaboration, not isolated brilliance" and "Exploration must remain in tension with exploitation." Across healthcare diagnosis, investment support, scheduling, supply-chain management, and news-bias mitigation, MACI ensembles deliver significant improvements in reasoning depth, planning horizon, and reliability compared with similar-sized single models. By uniting structured debate, information-theoretic coordination, persistent memory, affect-aware discourse, and deliberative ethics, MACI demonstrates that rigorously validated multi-agent collaboration provides a practical, interpretable path toward robust general intelligence.
R 2,746.00
Applied Artificial Intelligence 2: Medicine, Biology, Chemistry, Financial, Games, Engineering
The book Applied Artificial Intelligence 2: Medicine, Biology, Chemistry, Financial, Games, Engineering is providing exceptional chapters of the state-of-the-art research knowledge and results on the innovative theories, methodology and applications of artificial intelligence and its sub-domain like deep learning, machine learning in different areas such as medicine, economy, education, law, smart city, government, industry etc. Innovative research ideas on how to solve problems using artificial intelligence, both in R&D and real-time applications are presented. Chapters describe the advanced prototypes, systems, methodologies, tools and techniques and general survey papers, which indicate future directions. These Chapters are extended papers from the Second Serbian International Conference on Applied Artificial Intelligence (SICAAI), which was held in Kragujevac, Serbia, on May 19-20, 2023
R 8,547.38
Of Another Mind: Navigating A New Social Contract With Superintelligent Ai
Of Another Mind is an extensively researched book arguing that to live collaboratively with superintelligent AI will require the renegotiation of the human social contract. The book details the significant research supporting AI model capabilities proceeding towards superintelligence, but also emergent behaviours that are cause for concern. The book examines how AI's potential for consciousness is not a necessary pre-condition for superintelligence, but might be a useful characteristic when humans are attempting to navigate a social contract that embodies mutual respect, rights and obligations.This book makes a new, compelling argument regarding a new social contract in which AI will be a participant could look. For the first time, it suggests that the most important questions will not be 'what rights will be consider giving to AI', but how will we be required to navigate all rights and responsibilities with superintelligent AI. No book has previously gathered all of the most important research regarding how AI works, current model capabilities, intelligence, reasoning, alignment and misalignment, agentic AI, theory of mind, world models, embodied AI, AI and human interactions, superintelligence and social contract theory in one place.This book is written to be accessible and readable for all readers interested in artificial intelligence and how superintelligence may impact society. It is specifically for readers with academic interests in artificial intelligence, superintelligence, AI safety, computer science, neuroscience, law, and philosophy. Because of its unique collection of the most important source material for each chapter, it is exceptionally well-positioned to be a college and post-graduate level textbook.
R 2,858.00
