This book explores the subject of artificial psychology and how the field must adapt human neuro-psychological testing techniques to provide adequate cognitive testing of advanced artificial intelligence systems. It shows how classical testing methods will reveal nothing about the cognitive nature of the systems and whether they are learning, reasoning, and evolving correctly; for these systems, the authors outline how testing techniques similar to/adapted from human psychological testing must be adopted, particularly in understanding how the system reacts to failure or relearning something it has learned incorrectly or inferred incorrectly. The authors provide insights into future architectures/capabilities that artificial cognitive systems will possess and how we can evaluate how well they are functioning. It discusses at length the notion of human/AI communication and collaboration and explores such topics as knowledge development, knowledge modeling and ambiguity management, artificial cognition and self-evolution of learning, artificial brain components and cognitive architecture, and artificial psychological modeling. Explores the concepts of Artificial Psychology and Artificial Neuroscience as applied to advanced artificially cognitive systems; Provides insight into the world of cognitive architectures and biologically-based computing designs which will mimic human brain functionality in artificial intelligent systems of the future; Provides description and design of artificial psychological modeling to provide insight into how advanced artificial intelligent systems are learning and evolving; Explores artificial reasoning and inference architectures and the types of modeling and testing that will be required to "trust" an autonomous artificial intelligent systems.

Robots challenge humans' beliefs and expectations. Hence, regardless of whether they are the audience of a conference, the visitors of a lab, the citizens in general, some journalists, or the European Parliament, the first step in order to gain a better understanding of the field of robotics is obviously to consult the experts. Roboticists seem indeed to be in the best position to guide society in this matter, whether it is in the everyday life or within an official institution. Today however, there is a gap between the robots, as they are actually thought and built, and the intelligent and autonomous machines, as they are perceived by the society. How can we explain it? Do the words borrowed from the living organisms and used to describe robots play a role in the confusion about the status of the discipline of robotics? The texts gathered within this book focus on the problematic of wording robotics from various perspectives. They are the results of a unique interdisciplinary meeting gathering roboticists, linguists, philosophers and neuroscientists, the 4th Workshop of Anthropomorphic Motion Factory held at LAAS-CNRS in Toulouse on Nov 31st - Dec 1st 2017.

This book presents the Proceedings of The International Science and Technology Conference "FarEastCon-2018," which took place on October 2-4, 2018 in Vladivostok, Russian Federation. The conference provided a platform for accumulating expert opinion on projects and initiatives aimed at the implementation of far-sighted scientific research and development, and allowed current scientific and practical achievements to be shared with wide circle of researchers. Featuring selected papers from the conference, the book is of interest to a broad range of experts involved in developing innovative solutions and organizing events that increase the efficiency of economic and innovative activities.

What is mind? ""Can we build synthetic or artificial minds?"" Think these questions are only reserved for Science Fiction? Well, not anymore. This collection presents a diverse overview of where the development of artificial minds is as the twenty first century begins. Examined from nearly all viewpoints, Visions of Mind includes perspectives from philosophy, psychology, cognitive science, social studies and artificial intelligence. This collection comes largely as a result of many conferences and symposiums conducted by many of the leading minds on this topic. At the core is Professor Aaron Sloman's symposium from the spring 2000 UK Society for Artificial Intelligence conference. Authors from that symposium, as well as others from around the world have updated their perspectives and contributed to this powerful book. The result is a multi-disciplinary approach to the long term problem of designing a human-like mind, whether for scientific, social, or engineering purposes. The topics addressed within this text are valuable to both artificial intelligence and cognitive science, and also to the academic disciplines that they draw on and feed. Among those disciplines are philosophy, computer science, and psychology.

This book gathers revised and extended versions of the best papers presented at the 8th International Joint Conference on Computational Intelligence (IJCCI 2016), which was held in Porto, Portugal from 9 to 11 November 2016. The papers address three main fields of Computational Intelligence, namely: Evolutionary Computation, Fuzzy Computation, and Neural Computation. In addition to highlighting recent advances in these areas, the book offers veteran researchers new and innovative solutions, while also providing a source of information and inspiration for newcomers to the field.

One of the goals of artificial intelligence (AI) is creating autonomous agents that must make decisions based on uncertain and incomplete information. The goal is to design rational agents that must take the best action given the information available and their goals. Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions provides an introduction to different types of decision theory techniques, including MDPs, POMDPs, Influence Diagrams, and Reinforcement Learning, and illustrates their application in artificial intelligence. This book provides insights into the advantages and challenges of using decision theory models for developing intelligent systems.

This book presents a comprehensive definition of smart grids and their benefits, and compares smart and traditional grids. It also introduces a design methodology for stand-alone hybrid renewable energy system with and without applying the smart grid concepts for comparison purposes. It discusses using renewable energy power plants to feed loads in remote areas as well as in central power plants connected to electric utilities. Smart grid concepts used in the design of the hybrid renewable power systems can reduce the size of components, which can be translated to a reduction in the cost of generated energy. The proposed hybrid renewable energy system includes wind, photovoltaic, battery, and diesel, and is used initially to feed certain loads, covering the load required completely. The book introduces a novel methodology taking the smart grid concept into account by dividing the loads into high and low priority parts. The high priority part should be supplied at any generated conditions. However, the low priority loads can be shifted to the time when the generated energy from renewable energy sources is greater than the high priority loads requirements. The results show that the use of this smart grid concept reduces the component size and the cost of generated energy compared to that without dividing the loads. The book also describes the use of smart optimization techniques like particle swarm optimization (PSO) and genetic algorithm (GA) to optimally design the hybrid renewable energy system. This book provides an excellent background to renewable energy sources, optimal sizing and locating of hybrid renewable energy sources, the best optimization methodologies for sizing and designing the components of hybrid renewable energy systems, and offers insights into using smart grid concepts in the system's design and sizing. It also helps readers understand the dispatch methodology and how to connect the system's different components, their modeling, and the cost analysis of the system.

The book presents innovative scientific research works by academics, research scholars and students, presented at the 2017 International Conference on Energy, Materials and Information Technology at Amity University Jharkhand, India. It includes contributions on system solutions based on soft computing techniques, and covers innovative soft computing techniques and tools with advanced applications. A major focus of the book is on presenting interdisciplinary problems and how they can be solved using information technology, together with innovative connections to other disciplines. It also includes papers on cloud computing and WSN-related real-time research.

This book presents original, peer-reviewed research papers from the 4th Purple Mountain Forum -International Forum on Smart Grid Protection and Control (PMF2019-SGPC), held in Nanjing, China on August 17-18, 2019. Addressing the latest research hotspots in the power industry, such as renewable energy integration, flexible interconnection of large scale power grids, integrated energy system, and cyber physical power systems, the papers share the latest research findings and practical application examples of the new theories, methodologies and algorithms in these areas. As such book a valuable reference for researchers, engineers, and university students.

This contributed volume discusses diverse topics to demystify the rapidly emerging and evolving blockchain technology, the emergence of integrated platforms and hosted third-party tools, and the development of decentralized applications for various business domains. It presents various applications that are helpful for research scholars and scientists who are working toward identifying and pinpointing the potential of as well as the hindrances to this technology.

This book introduces readers to the use of R codes for optimization problems. First, it provides the necessary background to understand data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how to use them to solve optimization problems with R. Further, it discusses the main advantages of R in optimization problems, and provides R codes based on real-world data sets throughout. Offering a comprehensive review of DEA and fuzzy DEA models and the corresponding R codes, this practice-oriented reference guide is intended for masters and Ph.D. students in various disciplines, as well as practitioners and researchers.

Mapping and localization are two essential tasks in autonomous mobile robotics. Due to the unavoidable noise that sensors present, mapping algorithms usually rely on loop closure detection techniques, which entail the correct identification of previously seen places to reduce the uncertainty of the resulting maps. This book deals with the problem of generating topological maps of the environment using efficient appearance-based loop closure detection techniques. Since the quality of a visual loop closure detection algorithm is related to the image description method and its ability to index previously seen images, several methods for loop closure detection adopting different approaches are developed and assessed. Then, these methods are used in three novel topological mapping algorithms. The results obtained indicate that the solutions proposed attain a better performance than several state-of-the-art approaches. To conclude, given that loop closure detection is also a key component in other research areas, a multi-threaded image mosaicing algorithm is proposed. This approach makes use of one of the loop closure detection techniques previously introduced in order to find overlapping pairs between images and finally obtain seamless mosaics of different environments in a reasonable amount of time.

This book is a tribute to Julian Francis Miller's ideas and achievements in computer science, evolutionary algorithms and genetic programming, electronics, unconventional computing, artificial chemistry and theoretical biology. Leading international experts in computing inspired by nature offer their insights into the principles of information processing and optimisation in simulated and experimental living, physical and chemical substrates. Miller invented Cartesian Genetic Programming (CGP) in 1999, from a representation of electronic circuits he devised with Thomson a few years earlier. The book presents a number of CGP's wide applications, including multi-step ahead forecasting, solving artificial neural networks dogma, approximate computing, medical informatics, control engineering, evolvable hardware, and multi-objective evolutionary optimisations. The book addresses in depth the technique of 'Evolution in Materio', a term coined by Miller and Downing, using a range of examples of experimental prototypes of computing in disordered ensembles of graphene nanotubes, slime mould, plants, and reaction diffusion chemical systems. Advances in sub-symbolic artificial chemistries, artificial bio-inspired development, code evolution with genetic programming, and using Reed-Muller expansions in the synthesis of Boolean quantum circuits add a unique flavour to the content. The book is a pleasure to explore for readers from all walks of life, from undergraduate students to university professors, from mathematicians, computer scientists and engineers to chemists and biologists.

This book investigates observer-fault estimation techniques in detail, while also highlighting recent research and findings regarding fault estimation. Many practical control systems are subject to possible malfunctions, which may cause significant performance loss or even system instability. To improve the reliability, performance and safety of dynamical systems, fault diagnosis techniques are now receiving considerable attention, both in research and applications, and have been the subject of intensive investigations. Fault detection - the essential first step in fault diagnosis - is a binary decision-making process used to determine whether or not a fault has occurred. In turn, fault isolation is used to identify the location of the faulty component, while fault estimation is used to identify the size of the fault online. Compared with the problems involved in fault detection and isolation, fault estimation is considerably more challenging.

Cutting-edge research indicates that evolutionary programming is set to emerge as the dominant optimisation technique in the fast-changing power industry. Combining theory and practice, Intelligent System Applications in Power Engineering capitalises on the potential of neural networks and evolutionary computation to resolve real-world power engineering problems such as load forecasting, power system operation and planning optimisation. Unlike existing optimisation methods, these novel computational intelligence techniques provide power utilities with innovative solutions for improved performance. Features include:

• Introduction to evolutionary programming and neural networks serving as a foundation for later discussion of the benefits of hybrid systems
• Practical application of evolutionary programming to reactive power planning and dispatch for speedy, cost-effective increases in transmission capacity plus generator parameter estimation
• Examination of economic dispatch, power flow control in FACTS and co-generation scheduling and fault diagnosis for HVDC systems and transformers
• Consideration of power frequency and harmonic evaluation to maximise supply quality
• Employment of distance protection, faulty section estimation and calculation of fault clearing time for transient stability assessment

This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors' recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter.

This volume focuses on smart medical and healthcare systems (modern intelligent systems for medicine and healthcare) and includes 31 papers presenting recent trends and innovations in medicine and healthcare, including biomedical engineering research and technologies; machine learning and labeling for biomedical visual data analysis and understanding; advanced ICT for medicine and healthcare; and healthcare support systems. Innovation in medicine and healthcare is an interdisciplinary research area, which combines advanced technologies and problem-solving skills with medical and biological science, and smart medical and healthcare systems can provide efficient and accurate solution to problems faced by healthcare and medical practitioners today by using advanced information communication techniques, computational intelligence, mathematics, robotics and other advanced technologies. Discussing the techniques developed in this area, which will have a significant effect on future medicine and healthcare, the book is a valuable resource for researchers, students, engineers, and professionals working in the fields of medical systems, medical technology, and intelligent systems.

Due to increasing potential in real-world applications such as visual communications, computer assisted biomedical imaging, and video surveillance, image and video interpretations have become an area of growing interest. Intelligent Image and Video Interpretation: Algorithms and Applications covers all aspects of image and video analysis from low-level early visions to high-level recognition. This publication highlights how these techniques have become applicable and will prove to be a valuable tool for researchers, professionals, and graduate students working or studying the fields of imaging and video processing.

This book offers a detailed description of the histogram probabilistic multi-hypothesis tracker (H-PMHT), providing an accessible and intuitive introduction to the mathematical mechanics of H-PMHT as well as a definitive reference source for the existing literature on the method. Beginning with basic concepts, the authors then move on to address extensions of the method to a broad class of tracking problems. The latter chapters present applications using recorded data from experimental radar, sonar and video sensor systems. The book is supplemented with software that both furthers readers' understanding and acts as a toolkit for those who wish to apply the methods to their own problems.

Based on the idea of a universal rule for problem solving, the book suggests that the "System-Fuzzy Approach (SFA)" Model can be applied to various complex real-world problems. It is the first book for problem solving in complicated problems with a universal project management tool. Systematic searching is an essential step in identifying the right direction in problem solving; and the fuzzy steps in concrete problem solving reflect the flexibility and compromises involved in the process. Nevertheless, the fuzzy steps also demonstrate human beings' impressively flexible problem-solving skills. Simulating human decision-making processes based on fuzzy information processing is essential in our digital era, in which many problems need to be solved by means of artificial intelligence; hence the Fuzzy-AI Model emerged. As a universal rule and tool, it can be applied to a broad range of real-world problems. Offering a valuable guide to fuzzy decision-making, this book is intended for researchers, scientists and graduate students in the fields of Engineering, Economics, Sociology, Managerial Science, Project Management etc.

This book addresses new challenges and emerging ideas in Distributed Information Filtering and Retrieval. It gathers extended papers presented at DART 2013 (the 7th International Workshop on Information Filtering and Retrieval), held on December 6, 2013 in Turin, Italy, and co-hosted with the XIII International Conference of the Italian Association for Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. The papers presented here offer a comprehensive review of related work and state-of-the-art techniques. The authors - a mix of respected practitioners and researchers - share their findings on a range of topics, including data leak protection on text comparison, natural language processing, ambient intelligence, information retrieval and web portals, and knowledge management. All contributions were carefully reviewed by experts in the respective area, who also provided useful suggestions to improve the book's overall quality.

Wagman gives a broad, structured, and detailed account of advancing intellectual developments in both psychological and computational theories of the nature of problem- solving. Known for originating the PLATO computer-based Dilemma Counseling System, psychologist Wagman is the author of 17 books, including "Scientific Discovery Processes in Humans and Computers "(Praeger, 2000).

In this book, Professor Emeritus Morton Wagman gives a broad, structured, and detailed account of advancing intellectual developments in both psychological and computational theories of the nature of problem solving. Known for originating the PLATO computer-based Dilemma Counseling System, psychologist Wagman is the author of 17 books, including "Scientific Discovery Processes in Humans and Computers, "(Praeger, 2000)

Of special interest to readers will be Wagman's conclusion that artificial intelligence problem-solving systems are deepening and broadening theories of human problem solving from scientific to everyday approaches. Scholars and professionals in psychology, artificial intelligence, and cognitive science will consider this a volume a valuable addition to their collections.

This book contains 74 papers presented at ICTCS 2017: Third International Conference on Information and Communication Technology for Competitive Strategies. The conference was held during 16-17 December 2017, Udaipur, India and organized by Association of Computing Machinery, Udaipur Professional Chapter in association with The Institution of Engineers (India), Udaipur Local Center and Global Knowledge Research Foundation. This book contains papers mainly focused on ICT for Computation, Algorithms and Data Analytics and IT Security etc.