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The development of modern knowledge-based systems, for applications
ranging from medicine to finance, necessitates going well beyond
traditional rule-based programming. Frontiers of Expert Systems:
Reasoning with Limited Knowledge attempts to satisfy such a need,
introducing exciting and recent advances at the frontiers of the
field of expert systems. Beginning with the central topics of
logic, uncertainty and rule-based reasoning, each chapter in the
book presents a different perspective on how we may solve problems
that arise due to limitations in the knowledge of an expert
system's reasoner. Successive chapters address (i) the fundamentals
of knowledge-based systems, (ii) formal inference, and reasoning
about models of a changing and partially known world, (iii)
uncertainty and probabilistic methods, (iv) the expression of
knowledge in rule-based systems, (v) evolving representations of
knowledge as a system interacts with the environment, (vi) applying
connectionist learning algorithms to improve on knowledge acquired
from experts, (vii) reasoning with cases organized in indexed
hierarchies, (viii) the process of acquiring and inductively
learning knowledge, (ix) extraction of knowledge nuggets from very
large data sets, and (x) interactions between multiple specialized
reasoners with specialized knowledge bases. Each chapter takes the
reader on a journey from elementary concepts to topics of active
research, providing a concise description of several topics within
and related to the field of expert systems, with pointers to
practical applications and other relevant literature. Frontiers of
Expert Systems: Reasoning with Limited Knowledge is suitable as a
secondary text for a graduate-level course, and as a reference for
researchers and practitioners in industry.
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Modern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Syracuse, NY, USA, June 28 - July 1, 2011, Proceedings, Part II (Paperback, Edition.)
Kishan G. Mehrotra, Chilukuri Krishna Mohan, Jae C. Oh, Pramod K. Varshney, Moonis Ali
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R3,052
Discovery Miles 30 520
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Ships in 10 - 15 working days
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The two volume set LNAI 6703 and LNAI 6704 constitutes the
thoroughly refereed conference proceedings of the 24th
International Conference on Industrial Engineering and Other
Applications of Applied Intelligent Systems, IEA/AIE 2011, held in
Syracuse, NY, USA, in June/July 2011.
The total of 92 papers selected for the proceedings were carefully
reviewed and selected from 206 submissions. The papers cover a wide
number of topics including feature extraction, discretization,
clustering, classification, diagnosis, data refinement, neural
networks, genetic algorithms, learning classifier systems, Bayesian
and probabilistic methods, image processing, robotics, navigation,
optimization, scheduling, routing, game theory and agents,
cognition, emotion, and beliefs.
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Modern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Syracuse, NY, USA, June 28 - July 1, 2011, Proceedings, Part I (Paperback, Edition.)
Kishan G. Mehrotra, Chilukuri Krishna Mohan, Jae C. Oh, Pramod K. Varshney, Moonis Ali
|
R1,584
Discovery Miles 15 840
|
Ships in 10 - 15 working days
|
The two volume set LNAI 6703 and LNAI 6704 constitutes the
thoroughly refereed conference proceedings of the 24th
International Conference on Industrial Engineering and Other
Applications of Applied Intelligent Systems, IEA/AIE 2011, held in
Syracuse, NY, USA, in June/July 2011.
The total of 92 papers selected for the proceedings were carefully
reviewed and selected from 206 submissions. The papers cover a wide
number of topics including feature extraction, discretization,
clustering, classification, diagnosis, data refinement, neural
networks, genetic algorithms, learning classifier systems, Bayesian
and probabilistic methods, image processing, robotics, navigation,
optimization, scheduling, routing, game theory and agents,
cognition, emotion, and beliefs.
The development of modern knowledge-based systems, for applications
ranging from medicine to finance, necessitates going well beyond
traditional rule-based programming. Frontiers of Expert Systems:
Reasoning with Limited Knowledge attempts to satisfy such a need,
introducing exciting and recent advances at the frontiers of the
field of expert systems. Beginning with the central topics of
logic, uncertainty and rule-based reasoning, each chapter in the
book presents a different perspective on how we may solve problems
that arise due to limitations in the knowledge of an expert
system's reasoner. Successive chapters address (i) the fundamentals
of knowledge-based systems, (ii) formal inference, and reasoning
about models of a changing and partially known world, (iii)
uncertainty and probabilistic methods, (iv) the expression of
knowledge in rule-based systems, (v) evolving representations of
knowledge as a system interacts with the environment, (vi) applying
connectionist learning algorithms to improve on knowledge acquired
from experts, (vii) reasoning with cases organized in indexed
hierarchies, (viii) the process of acquiring and inductively
learning knowledge, (ix) extraction of knowledge nuggets from very
large data sets, and (x) interactions between multiple specialized
reasoners with specialized knowledge bases. Each chapter takes the
reader on a journey from elementary concepts to topics of active
research, providing a concise description of several topics within
and related to the field of expert systems, with pointers to
practical applications and other relevant literature. Frontiers of
Expert Systems: Reasoning with Limited Knowledge is suitable as a
secondary text for a graduate-level course, and as a reference for
researchers and practitioners in industry.
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