Interfaces
Predicting demonstrations' violence level using qualitative reasoning
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Formalization of treatment guidelines using Fuzzy Cognitive Maps and semantic web tools
Journal of Biomedical Informatics
Towards qualitative reasoning for policy decision support in demonstrations
AAMAS'11 Proceedings of the 10th international conference on Advanced Agent Technology
Towards Hebbian learning of Fuzzy Cognitive Maps in pattern classification problems
Expert Systems with Applications: An International Journal
A proactive balanced scorecard
International Journal of Information Management: The Journal for Information Professionals
Bagged nonlinear hebbian learning algorithm for fuzzy cognitive maps working on classification tasks
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
Fuzzy cognitive strategic maps in business process performance measurement
Expert Systems with Applications: An International Journal
A cognitive WSN framework for highway safety based on weighted cognitive maps and Q-learning
Proceedings of the second ACM international symposium on Design and analysis of intelligent vehicular networks and applications
A fuzzy cognitive map of the psychosocial determinants of obesity
Applied Soft Computing
RuleML representation and simulation of Fuzzy Cognitive Maps
Expert Systems with Applications: An International Journal
A dynamic fuzzy cognitive map applied to chemical process supervision
Engineering Applications of Artificial Intelligence
Using qualitative reasoning for social simulation of crowds
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
Modeling maintenance projects risk effects on ERP performance
Computer Standards & Interfaces
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The theory of cognitive maps was developed in 1976. Its main aim was the representation of (causal) relationships among concepts also known as factors or nodes. Concepts could be assigned values. Causal relationships between two concepts could be of three types: positive, negative or neutral. Increase in the value of a concept would yield a corresponding positive or negative increase at the concepts connected to it via relationships. In 1986 Bart Kosko introduced the notion of fuzziness to cognitive maps and created the theory of Fuzzy Cognitive Maps (FCMs). The relationship between two concepts in (FCMs) can take a value in the interval [-1,1]. This relationship value is called weight. For the last twenty years extensive research in the theory of FCMs has been performed that provided major improvements and enhancements in its theoretical underpinning. New methodologies and approaches have been developed. FCMs have also been applied to many different sectors. New software tools have been developed that automate FCM creation and management. The aim of this book is to present recent advances and state of the art in FCM theory, methodologies, applications and tools that exist to date scattered in journal papers, in a concrete and integrated manner.