Using artificial intelligence and robustness as a unifying theme, this book comments on the fundamental strategies found in nature (such as redundancy, granularity, adaptation, repair, self-healing, etc.), and how an understanding ofthese can be used to further research into general design principles for artificial intelligence in the context of a diverse range of modern research areasand systems (including pervasive computing, autonomic computing, ambient intelligence, bioinformatics and others). Contributions from experts in the field provide an invaluable insight into a variety of cutting-edge research areas using artificial intelligence and robustness as the central theme. Practitionersin various fields will gain an insight into the important role robustness plays in natural and artificial systems in general, and in artificial intelligence in particular. Reflects the increasing interest in the importance of robustness as a design principle for AI. Draws on strategies and examples of problem solving from nature (such as redundancy, granularity, adaptation etc,) inthe design of robust systems. INDICE: From the contents Part 1 Robustness in Computer Hardware, Software, Networks and Protocols.- Robustness in Digital Hardware.- Multiagent-Based fault Tolerance Management for Robustness.- A Two-Level Robustness Model for Self-Managing Software Systems.- Robustness in Network Protocols and DistributedApplications of the Internet.- Part II Robustness in Biology Inspired Systems.- Detecting Danger: The Dendrtic Cell Algorithm.- Non-invasiveBrain-Computer Interfaces for Semi-Autonomous Assistive Devices.- Robust Learning of High-Dimensional Biological Networks with Bayesian Networks.- Part III Robustness in Artificial Intelligence Systems.
- ISBN: 978-1-84800-260-9
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 330
- Fecha Publicación: 01/08/2008
- Nº Volúmenes: 1
- Idioma: Inglés