Future Directions for Intelligent Systems and Information Sciences
Future Directions for Intelligent Systems and Information Sciences

Author: Nikola Kasabov

Publisher: Physica

Published: 2013-11-11

Total Pages: 411

ISBN-13: 3790818569

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This edited volume comprises invited chapters that cover five areas of the current and the future development of intelligent systems and information sciences. Half of the chapters were presented as invited talks at the Workshop "Future Directions for Intelligent Systems and Information Sciences" held in Dunedin, New Zealand, 22-23 November 1999 after the International Conference on Neuro-Information Processing (lCONIPI ANZIISI ANNES '99) held in Perth, Australia. In order to make this volume useful for researchers and academics in the broad area of information sciences I invited prominent researchers to submit materials and present their view about future paradigms, future trends and directions. Part I contains chapters on adaptive, evolving, learning systems. These are systems that learn in a life-long, on-line mode and in a changing environment. The first chapter, written by the editor, presents briefly the paradigm of Evolving Connectionist Systems (ECOS) and some of their applications. The chapter by Sung-Bae Cho presents the paradigms of artificial life and evolutionary programming in the context of several applications (mobile robots, adaptive agents of the WWW). The following three chapters written by R.Duro, J.Santos and J.A.Becerra (chapter 3), GCoghill . (chapter 4), Y.Maeda (chapter 5) introduce new techniques for building adaptive, learning robots.

From Motor Learning to Interaction Learning in Robots
From Motor Learning to Interaction Learning in Robots

Author: Olivier Sigaud

Publisher: Springer

Published: 2012-05-04

Total Pages: 538

ISBN-13: 9783642262326

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From an engineering standpoint, the increasing complexity of robotic systems and the increasing demand for more autonomously learning robots, has become essential. This book is largely based on the successful workshop “From motor to interaction learning in robots” held at the IEEE/RSJ International Conference on Intelligent Robot Systems. The major aim of the book is to give students interested the topics described above a chance to get started faster and researchers a helpful compandium.

An A-Z of Genetic Factors in Autism
An A-Z of Genetic Factors in Autism

Author: Kenneth Aitken

Publisher: Jessica Kingsley Publishers

Published: 2011-04-15

Total Pages: 546

ISBN-13: 0857004905

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Our understanding of the biological bases to the autistic spectrum disorders (ASDs) is advancing rapidly. Over 80 genetic conditions have now been reported in people who have also been diagnosed with ASDs. Many of these conditions have specific implications for the presenting phenotype and for treatment, management, and intervention. If the basis to the presenting behavioural phenotype is not identified, this can result in a sub-optimal level of care, complications, or even permanent damage. Kenneth J. Aitken shows that the notion of a single condition known as 'autism' is no longer tenable, and challenges current trends in the diagnosis and management of these behaviours as a homogenous group by drawing on recent research into brain function, genetics, epidemiology and neurology. This volume explains the biology and genetics of ASD, and provides clinicians and researchers with a comprehensive summary of each genetic factor including the research that links it to ASD, diagnosis and treatment issues, and related animal models, as well as detailing relevant professional organisations and avenues for further research. An A-Z of Genetic Factors in Autism is an essential resource for a wide range of researchers, clinical professionals and students interested in autism spectrum disorders, including clinical and educational psychologists, dieticians, psychiatrists, and neurologists.

Innovations in Neural Information Paradigms and Applications
Innovations in Neural Information Paradigms and Applications

Author: Monica Bianchini

Publisher: Springer Science & Business Media

Published: 2009-10-16

Total Pages: 297

ISBN-13: 3642040020

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Tremendous advances in all disciplines including engineering, science, health care, business, avionics, management, and so on, can also be attributed to the development of artificial intelligence paradigms. In fact, researchers are always interested in desi- ing machines which can mimic the human behaviour in a limited way. Therefore, the study of neural information processing paradigms have generated great interest among researchers, in that machine learning, borrowing features from human intelligence and applying them as algorithms in a computer friendly way, involves not only Mathem- ics and Computer Science but also Biology, Psychology, Cognition and Philosophy (among many other disciplines). Generally speaking, computers are fundamentally well-suited for performing au- matic computations, based on fixed, programmed rules, i.e. in facing efficiently and reliably monotonous tasks, often extremely time-consuming from a human point of view. Nevertheless, unlike humans, computers have troubles in understanding specific situations, and adapting to new working environments. Artificial intelligence and, in particular, machine learning techniques aim at improving computers behaviour in tackling such complex tasks. On the other hand, humans have an interesting approach to problem-solving, based on abstract thought, high-level deliberative reasoning and pattern recognition. Artificial intelligence can help us understanding this process by recreating it, then potentially enabling us to enhance it beyond our current capabilities.

Designing Autonomous Agents
Designing Autonomous Agents

Author: Pattie Maes

Publisher: MIT Press

Published: 1990

Total Pages: 212

ISBN-13: 9780262631358

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Designing Autonomous Agents provides a summary and overview of the radically different architectures that have been developed over the past few years for organizing robots. These architectures have led to major breakthroughs that promise to revolutionize the study of autonomous agents and perhaps artificial intelligence in general. The new architectures emphasize more direct coupling of sensing to action, distributedness and decentralization, dynamic interaction with the environment, and intrinsic mechanisms to cope with limited resources and incomplete knowledge. The research discussed here encompasses such important ideas as emergent functionality, task-level decomposition, and reasoning methods such as analogical representations and visual operations that make the task of perception more realistic. Contents A Biological Perspective on Autonomous Agent Design, Randall D. Beer, Hillel J. Chiel, Leon S. Sterling * Elephants Don't Play Chess, Rodney A. Brooks * What Are Plans For? Philip E. Agre and David Chapman * Action and Planning in Embedded Agents, Leslie Pack Kaelbling and Stanley J. Rosenschein * Situated Agents Can Have Goals, Pattie Maes * Exploiting Analogical Representations, Luc Steels * Internalized Plans: A Representation for Action Resources, David W. Payton * Integrating Behavioral, Perceptual, and World Knowledge in Reactive Navigation, Ronald C. Arkin * Symbol Grounding via a Hybrid Architecture in an Autonomous Assembly System, Chris Malcolm and Tim Smithers * Animal Behavior as a Paradigm for Developing Robot Autonomy, Tracy L. Anderson and Max Donath