Cognitive Robotics Control
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Cognitive Robotics & Control
Robotics and control are both research and application domains that have been frequently engineered through the use of interdisciplinary approaches like cybernetics. Cognition is a particular concept of this approach, abstracted from the context of living organisms to that of artificial devices, and is concerned with knowledge acquisition and understanding through thought, experience, and the senses. Cognitive robotics and control refer to knowledge processing as much as knowledge generation from problem understanding, leading to special forms of architectures that enable systems to behave in an autonomous way. The main aim of this book is to highlight emerging applications and address recent breakthroughs in the domain of cognitive robotics and control and related areas. Procedures, algorithms, architectures, and implementations for reasoning, problem solving, or decision making are considered in the domain of robotics and control.
Cognitive Robotics
The current state of the art in cognitive robotics, covering the challenges of building AI-powered intelligent robots inspired by natural cognitive systems. A novel approach to building AI-powered intelligent robots takes inspiration from the way natural cognitive systems—in humans, animals, and biological systems—develop intelligence by exploiting the full power of interactions between body and brain, the physical and social environment in which they live, and phylogenetic, developmental, and learning dynamics. This volume reports on the current state of the art in cognitive robotics, offering the first comprehensive coverage of building robots inspired by natural cognitive systems. Contributors first provide a systematic definition of cognitive robotics and a history of developments in the field. They describe in detail five main approaches: developmental, neuro, evolutionary, swarm, and soft robotics. They go on to consider methodologies and concepts, treating topics that include commonly used cognitive robotics platforms and robot simulators, biomimetic skin as an example of a hardware-based approach, machine-learning methods, and cognitive architecture. Finally, they cover the behavioral and cognitive capabilities of a variety of models, experiments, and applications, looking at issues that range from intrinsic motivation and perception to robot consciousness. Cognitive Robotics is aimed at an interdisciplinary audience, balancing technical details and examples for the computational reader with theoretical and experimental findings for the empirical scientist.
Innovations in Applied Artificial Intelligence
“Intelligent systems must perform in order to be in demand. ” Intelligent systems technology is being applied steadily in solving many day-to-day problems. Each year the list of real-world deployed applications that inconspicuously host the results of research in the area grows considerably. These applications are having a significant impact in industrial operations, in financial circles, in transportation, in education, in medicine, in consumer products, in games and elsewhere. A set of selected papers presented at the seventeenth in the series of conferences on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2004), sponsored by the International Society of Applied Intelligence, is offered in this manuscript. These papers highlight novel applications of the technology and show how new research could lead to new and innovative applications. We hope that you find these papers to be educational, useful in your own research, and stimulating. In addition, we have introduced some special sessions to emphasize a few areas of artificial intelligence (AI) that are either relatively new, have received considerable attention recently or perhaps have not yet been represented well. To this end, we have included special sessions on e-learning, bioinformatics, and human-robot interaction (HRI) to complement the usual offerings in areas such as data mining, machine learning, intelligent systems, neural networks, genetic algorithms, autonomous agents, natural language processing, intelligent user interfaces, evolutionary computing, fuzzy logic, computer vision and image processing, reasoning, heuristic search, security, Internet applications, constraint satisfaction problems, design, and expert systems.