The contributions to this book are from Artificial Intelligence specialists from all over the world. Their ideas on the future of AI are original, thought-provoking and sometimes controversial. The first section, Methodology, looks at how AI students should be educated, AI's relationship to computer science, and specialisation. The next part discusses the paradigms that dominated AI research in the past (such as the symbol processing paradigm) and a perceived need for new paradigms. Trends outlines the state of the art and trends in knowledge representation, intelligent interfaces, intelligent networking systems, and distributed AI. The fourth part, Prospects, looks further into the future, suggesting important research topics and the future of AI research in general. An important question is asked: Why should anybody use AI technology anyway?
The contributions to this book are from Artificial Intelligence specialists from all over the world. Their ideas on the future of AI are original, thought-provoking and sometimes controversial. The first section, Methodology, looks at how AI students should be educated, AI's relationship to computer science, and specialisation. The next part discusses the paradigms that dominated AI research in the past (such as the symbol processing paradigm) and a perceived need for new paradigms. Trends outlines the state of the art and trends in knowledge representation, intelligent interfaces, intelligent networking systems, and distributed AI. The fourth part, Prospects, looks further into the future, suggesting important research topics and the future of AI research in general. An important question is asked: Why should anybody use AI technology anyway?
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Technology
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Illustrationen
Maße
ISBN-13
978-0-444-89048-1 (9780444890481)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Klassifikation
Methodology. The Need for a Formal Education in Artificial Intelligence (R.B. Banerji). Informatics as the Scientific Environment for Artificial Intelligence (J. Gruska). Towards a Reintegration of Artificial Intelligence Research (J.F. Sowa). Paradigms. Paradigm Shifts in Artificial Intelligence (A. de Callatay). Why Today's Computers Don't Learn the Way People Do (W.J. Clancey). Future Directions of Artificial Intelligence in a Resource-Limited Environment (R.S. Michalski, D.C. Littman). Beyond the Symbolic Paradigm (L.S. Sterling, R.D. Beer, H.J. Chiel). Trends. Research Trends in Knowledge Representation (L.C. Aiello, D. Nardi). "Artificial" Interfaces for Knowledge Acquisition: A Futuristic Scenario (R. Chandrasekar, S. Ramani). Intelligent Distributed and Networking Systems (J. Maitan). Distributed Artificial Intelligence (Zhongzhi Shi). Prospects. On the Future (and Present) State of Artificial Intelligence (Y. Kodratoff). Artificial Intelligence Needs its Eisenstein and Chaplin (A. Markus, E. Knuth). AI Technology, Non-Existent or Extinct? (P. van Lith). The Future of Research in Artificial Intelligence (L. Siklossy). Epilogue. The Dialectics of Artificial Intelligence (P.A. Flach). References. Index.
