Heuristic Search Applied to Fuzzy Cognitive Maps Learning

Fuzzy Cognitive Maps were initially proposed by Kosko [1–3], as an extension of cognitive maps proposed by Axelrod [4]. FCM is a graph used for representing causal relationships among concepts that stand for the states and variables of the system, emulating the cognitive knowledge of experts on a specific area. FCM can be interpreted as a combination of Fuzzy Logic and Neural Networks, because it combines the sense rules of Fuzzy Logic with the learning of the Neural Networks. A FCM describes the behavior of a knowledge based system in terms of concepts, where each concept represents an entity, a state, a variable, or a characteristic of the system. The human knowledge and experience about the system determines the type and the number of the nodes as well as the initial conditions of the FCM.

[1]  Andreas S. Andreou,et al.  Soft computing for crisis management and political decision making: the use of genetically evolved fuzzy cognitive maps , 2005, Soft Comput..

[2]  Elpiniki I. Papageorgiou,et al.  Learning Algorithms for Fuzzy Cognitive Maps—A Review Study , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[3]  Bart Kosko,et al.  Fuzzy Engineering , 1996 .

[4]  Michael N. Vrahatis,et al.  Fuzzy Cognitive Maps Learning Using Particle Swarm Optimization , 2005, Journal of Intelligent Information Systems.

[5]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[6]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[7]  Michael N. Vrahatis,et al.  A first study of fuzzy cognitive maps learning using particle swarm optimization , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[8]  Chrysostomos D. Stylios,et al.  Active Hebbian learning algorithm to train fuzzy cognitive maps , 2004, Int. J. Approx. Reason..

[9]  Voula C. Georgopoulos,et al.  Fuzzy cognitive map architectures for medical decision support systems , 2008, Appl. Soft Comput..

[10]  Zhu Yanchun,et al.  An Integrated Framework for Learning Fuzzy Cognitive Map using RCGA and NHL Algorithm , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.

[11]  P. N. Suganthan,et al.  Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.

[12]  R. Axelrod.  Structure of decision : the cognitive maps of political elites , 2015 .

[13]  R. Storn,et al.  Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .

[14]  Elpiniki I. Papageorgiou,et al.  A new hybrid method using evolutionary algorithms to train Fuzzy Cognitive Maps , 2005, Appl. Soft Comput..

[15]  Dimitris E. Koulouriotis,et al.  Comparing simulated annealing and genetic algorithm in learning FCM , 2007, Appl. Math. Comput..

[16]  Karl Perusich,et al.  Fuzzy cognitive maps for policy analysis , 1996, 1996 International Symposium on Technology and Society Technical Expertise and Public Decisions. Proceedings.

[17]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[18]  Mostafa Jafari,et al.  Learning FCM by Tabu Search , 2007 .

[19]  Chrysostomos D. Stylios,et al.  An integrated two-level hierarchical system for decision making in radiation therapy based on fuzzy cognitive maps , 2003, IEEE Transactions on Biomedical Engineering.

[20]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[21]  Witold Pedrycz,et al.  Genetic learning of fuzzy cognitive maps , 2005, Fuzzy Sets Syst..

[22]  Rod Taber,et al.  Knowledge processing with Fuzzy Cognitive Maps , 1991 .

[23]  Bart Kosko,et al.  Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence , 1991 .

[24]  Randy L. Haupt,et al.  Practical Genetic Algorithms , 1998 .

[25]  Adil Baykasoglu,et al.  Training Fuzzy Cognitive Maps via Extended Great Deluge Algorithm with applications , 2011, Comput. Ind..

[26]  Michael Glykas.  Fuzzy Cognitive Maps: Advances in Theory, Methodologies, Tools and Applications , 2010 .

[27]  Bart Kosko,et al.  Virtual Worlds as Fuzzy Cognitive Maps , 1993, Presence: Teleoperators & Virtual Environments.