Fuzzy engineering
Causal Maps: Theory, Implementation, and Practical Applications in Multiagent Environments
IEEE Transactions on Knowledge and Data Engineering
China's E-Science Knowledge Grid Environment
IEEE Intelligent Systems
A contextual fuzzy cognitive map framework for geographic information systems
IEEE Transactions on Fuzzy Systems
Contextual fuzzy cognitive map for decision support in geographic information systems
IEEE Transactions on Fuzzy Systems
On causal inference in fuzzy cognitive maps
IEEE Transactions on Fuzzy Systems
Dynamical cognitive network - an extension of fuzzy cognitive map
IEEE Transactions on Fuzzy Systems
Knowledge acquisition based on the global concept of fuzzy cognitive maps
GCC'05 Proceedings of the 4th international conference on Grid and Cooperative Computing
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Knowledge representation and reasoning is a key issue of the Knowledge Grid. This paper proposes a Knowledge Map (KM) model for representing and reasoning causal knowledge as an overlay in the Knowledge Grid. It extends Fuzzy Cognitive Maps (FCMs) to represent and reason not only simple cause-effect relations, but also time-delay causal relations, conditional probabilistic causal relations and sequential relations. The mathematical model and dynamic behaviors of KM are presented. Experiments show that, under certain conditions, the dynamic behaviors of KM can translate between different states. Knowing this condition, experts can control or modify the constructed KM while its dynamic behaviors do not accord with their expectation. Simulations and applications show that KM is more powerful and natural than FCM in emulating real world.