Frontiers of Expert Systems: Reasoning with Limited KnowledgeSpringer Science & Business Media, 2012 M12 6 - 303 pages 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. |
Contents
| 1 | |
| 7 | |
| 8 | |
at Syracuse University since 1990 I apologize for errors particularly if I have | 9 |
Practical Reasoning | 23 |
Rule Based Programming | 98 |
5 | 107 |
8 | 115 |
Bibliography | 173 |
Case Based Reasoning Systems | 177 |
Uncertainty | 209 |
Bibliography | 233 |
2 | 250 |
12 | 256 |
Distributed Experts | 259 |
| 297 | |
Other editions - View all
Frontiers of Expert Systems: Reasoning With Limited Knowledge Chilukuri K. Mohan Limited preview - 2000 |
Frontiers of Expert Systems: Reasoning with Limited Knowledge Chilukuri Krishna Mohan No preview available - 2013 |
Common terms and phrases
adaptation agents analysis applied approach Artificial Intelligence associated assumptions attribute blackboard blackboard systems C₁ case-based reasoning CBR system Chapter classification tree classifier systems clustering components computations conditional independence connection weights connectionist connectionist expert system contains context corresponding data elements data mining database decision denote described determine developed discussed domain environment evaluate evidence Example execution Figure formulas function fuzzy Genetic Algorithms Global_clock goal hand side hypotheses ID3 algorithm identifying inference engine input interaction International Conf involves itemsets knowledge acquisition language layer learning algorithm Machine Learning MACIE matching modify Morgan Kaufmann multiple neural network output patterns payoff perform personal constructs possible posterior probability problem Proc programming relevant repertory grid represent representation retrieved rule firing rule-based expert systems rule-based programming rule-based system Section sequence solution solving specific strategy string structure subsets task temporal logic tion Truth maintenance systems values variables