NEURAL NETWORK MODELS Feedforward neural networks Recurrent neural networks Self-organizing maps Radial basis function networks Attractor neural networks and associative memory Modular networks Fuzzy neural networks Spiking neural networks Reservoir networks (echo-state networks, liquid-state machines, etc.) Large-scale neural networks Other topics in artificial neural networks FUZZY SETS AND SYSTEMS Mathematical and theoretical foundations of fuzzy sets, fuzzy measures, and fuzzy integrals Interpretable and Interactive approaches to uncertainty in AI Fuzzy data analysis, fuzzy clustering, classification and pattern recognition Type-2 fuzzy sets, computing with words, and granular computing Fuzzy systems design and optimization Applications of fuzzy sets and systems, fuzzy measures and integrals Fuzzy and uncertain information processing, information extraction, and fusion Theory and applications of imprecise probabilities and possibilities Neuro- and evolutionary-fuzzy systems EVOLUTIONARY COMPUTATION Ant colony optimization Particle swarm optimization Genetic algorithms Differential evolution Parallel and distributed algorithms Meta-modeling and surrogate models Evolutionary simulation-based optimization Discrete and combinatorial optimization Multi-objective evolutionary algorithms Evolutionary computation theory Evolutionary programming Evolved neural networks Evolutionary fuzzy systems Evolved neuro-fuzzy systems MACHINE LEARNING Unsupervised learning and clustering, (including PCA, and ICA) Reinforcement learning Probabilistic and information-theoretic methods Support vector machines and kernel methods EM algorithms Mixture models, ensemble learning, and other meta-learning or committee algorithms Bayesian, belief, causal, and semantic networks Statistical and pattern recognition algorithms Visualization of data Feature selection, extraction, and aggregation Hybrid learning methods Deep learning Other topics in machine learning | 