0
Your cart

Your cart is empty

Browse All Departments
  • All Departments
Price
  • R2,500 - R5,000 (4)
  • -
Status
Brand

Showing 1 - 4 of 4 matches in All Departments

Mathematical Models for Handling Partial Knowledge in Artificial Intelligence (Hardcover, 1995 ed.): Giulianella Coletti,... Mathematical Models for Handling Partial Knowledge in Artificial Intelligence (Hardcover, 1995 ed.)
Giulianella Coletti, Didier Dubois, R. Scozzafava
R4,572 Discovery Miles 45 720 Ships in 12 - 17 working days

Knowledge acquisition is one of the most important aspects influencing the quality of methods used in artificial intelligence and the reliability of expert systems. The various issues dealt with in this volume concern many different approaches to the handling of partial knowledge and to the ensuing methods for reasoning and decision making under uncertainty, as applied to problems in artificial intelligence. The volume is composed of the invited and contributed papers presented at the Workshop on Mathematical Models for Handling Partial Knowledge in Artificial Intelligence, held at the Ettore Majorana Center for Scientific Culture of Erice (Sicily, Italy) on June 19-25, 1994, in the framework of the International School of Mathematics "G.Stampacchia." It includes also a transcription of the roundtable held during the workshop to promote discussions on fundamental issues, since in the choice of invited speakers we have tried to maintain a balance between the various schools of knowl edge and uncertainty modeling. Choquet expected utility models are discussed in the paper by Alain Chateauneuf: they allow the separation of perception of uncertainty or risk from the valuation of outcomes, and can be of help in decision mak ing. Petr Hajek shows that reasoning in fuzzy logic may be put on a strict logical (formal) basis, so contributing to our understanding of what fuzzy logic is and what one is doing when applying fuzzy reasoning."

Probabilistic Logic in a Coherent Setting (Hardcover, 2002 ed.): Giulianella Coletti, R. Scozzafava Probabilistic Logic in a Coherent Setting (Hardcover, 2002 ed.)
Giulianella Coletti, R. Scozzafava
R3,102 Discovery Miles 31 020 Ships in 10 - 15 working days

The approach to probability theory followed in this book (which differs radically from the usual one, based on a measure-theoretic framework) characterizes probability as a linear operator rather than as a measure, and is based on the concept of coherence, which can be framed in the most general view of conditional probability. It is a flexible' and unifying tool suited for handling, e.g., partial probability assessments (not requiring that the set of all possible outcomes' be endowed with a previously given algebraic structure, such as a Boolean algebra), and conditional independence, in a way that avoids all the inconsistencies related to logical dependence (so that a theory referring to graphical models more general than those usually considered in bayesian networks can be derived). Moreover, it is possible to encompass other approaches to uncertain reasoning, such as fuzziness, possibility functions, and default reasoning.
The book is kept self-contained, provided the reader is familiar with the elementary aspects of propositional calculus, linear algebra, and analysis.

Mathematical Models for Handling Partial Knowledge in Artificial Intelligence (Paperback, Softcover reprint of the original 1st... Mathematical Models for Handling Partial Knowledge in Artificial Intelligence (Paperback, Softcover reprint of the original 1st ed. 1995)
Giulianella Coletti, Didier Dubois, R. Scozzafava
R4,448 Discovery Miles 44 480 Ships in 10 - 15 working days

Knowledge acquisition is one of the most important aspects influencing the quality of methods used in artificial intelligence and the reliability of expert systems. The various issues dealt with in this volume concern many different approaches to the handling of partial knowledge and to the ensuing methods for reasoning and decision making under uncertainty, as applied to problems in artificial intelligence. The volume is composed of the invited and contributed papers presented at the Workshop on Mathematical Models for Handling Partial Knowledge in Artificial Intelligence, held at the Ettore Majorana Center for Scientific Culture of Erice (Sicily, Italy) on June 19-25, 1994, in the framework of the International School of Mathematics "G.Stampacchia." It includes also a transcription of the roundtable held during the workshop to promote discussions on fundamental issues, since in the choice of invited speakers we have tried to maintain a balance between the various schools of knowl edge and uncertainty modeling. Choquet expected utility models are discussed in the paper by Alain Chateauneuf: they allow the separation of perception of uncertainty or risk from the valuation of outcomes, and can be of help in decision mak ing. Petr Hajek shows that reasoning in fuzzy logic may be put on a strict logical (formal) basis, so contributing to our understanding of what fuzzy logic is and what one is doing when applying fuzzy reasoning."

Probabilistic Logic in a Coherent Setting (Paperback, Softcover reprint of the original 1st ed. 2002): Giulianella Coletti, R.... Probabilistic Logic in a Coherent Setting (Paperback, Softcover reprint of the original 1st ed. 2002)
Giulianella Coletti, R. Scozzafava
R3,273 Discovery Miles 32 730 Ships in 10 - 15 working days

The approach to probability theory followed in this book (which differs radically from the usual one, based on a measure-theoretic framework) characterizes probability as a linear operator rather than as a measure, and is based on the concept of coherence, which can be framed in the most general view of conditional probability. It is a flexible' and unifying tool suited for handling, e.g., partial probability assessments (not requiring that the set of all possible outcomes' be endowed with a previously given algebraic structure, such as a Boolean algebra), and conditional independence, in a way that avoids all the inconsistencies related to logical dependence (so that a theory referring to graphical models more general than those usually considered in bayesian networks can be derived). Moreover, it is possible to encompass other approaches to uncertain reasoning, such as fuzziness, possibility functions, and default reasoning.
The book is kept self-contained, provided the reader is familiar with the elementary aspects of propositional calculus, linear algebra, and analysis.

Free Delivery
Pinterest Twitter Facebook Google+
You may like...
Loot
Nadine Gordimer Paperback  (2)
R205 R168 Discovery Miles 1 680
Higher
Michael Buble CD  (1)
R482 Discovery Miles 4 820
Efekto 77300-G Nitrile Gloves (M)(Green)
R63 Discovery Miles 630
Xbox One Replacement Case
 (8)
R53 Discovery Miles 530
Bosch GBM 320 Professional Drill…
R799 R728 Discovery Miles 7 280
Loot
Nadine Gordimer Paperback  (2)
R205 R168 Discovery Miles 1 680
Huntlea Original Two Tone Pillow Bed…
R650 R565 Discovery Miles 5 650
Casio LW-200-7AV Watch with 10-Year…
R999 R884 Discovery Miles 8 840
Johnny English
Rowan Atkinson, John Malkovich, … DVD  (1)
R51 R29 Discovery Miles 290
Zap! Kawaii Rock Painting Kit
Kit R250 R195 Discovery Miles 1 950

 

Partners