Technologies for Constructing Intelligent Systems 1 Tasks

Intelligent systems enhance the capacities made available by the internet and other computer-based technologies. This book deals with the theory behind the solutions to difficult problems in the construction of intelligent systems. Particular attention is paid to situations in which the available information and data may be imprecise, uncertain, incomplete or of linguistic nature. Various methodologies for these cases are discussed, among which are probabilistic, possibilistic, fuzzy, logical, evidential and network-based frameworks. One purpose of the book is to consider how these methods can be used cooperatively. Topics included in the book include fundamental issues in uncertainty, the rapidly emerging discipline of information aggregation, neural networks, bayesian networks and other network methods, as well as logic-based systems.

Computing with Words.- A new direction in AI: Toward a computational theory of perceptions.- Combining fuzzy and case-based reasoning to generate human-like music performances.- A fuzzy-rough approach to the representation of linguistic hedges.- Dealing with imprecise inputs in a fuzzy rule-based system using an implication-based rule model.- Constructing rough mereological granules of classifying rules and classifying algorithms.- Criticality in the network with imprecise activity times.- Object-oriented implementation of a model for fuzzy temporal reasoning.- A symbolic approach to syllogistic reasoning.- On algebraic foundations of information granulation.- Decision and Preferences.- On the issue of consistency in dynamical consensual aggregation.- A group decision support system based on linguistic multicriteria assessments.- Integral representations and decision theory.- Can qualitative utility criteria obey the sure thing principle?.- Pseudo-additive measures and the independence of events.- On discrete preference structures.- Families of valued sets as media.- A general framework for ordering fuzzy sets.- Learning, Classification and Clustering.- Pattern extraction method for text classification.- A comparison of rough set strategies for pre-term birth data.- Toward the intelligent control of hierarchical clustering.- Combining both a fuzzy inductive learning and a fuzzy repertory grid method.- An approach to computational microtexture perceptual detection with management of uncertainty.- Bagging improves uncertainty representation in evidential pattern classification.- Non-Euclidean genetic FCM clustering algorithm.- Different approaches to induce cooperation in fuzzy linguistic models under the COR methodology.- Retrieval of Information.- Evaluation of flexiblequeries: The quantified statement case.- Intelligent filtering with genetic algorithms and fuzzy logic.- Using semantic and phonetic term similarity for spoken document retrieval and spoken query processing.- Knowledge-based extrapolation of cases: A possibilistic approach.- A methodology to improve object oriented database systems with fuzzy types.