Titlebook: Computational Methods in Neural Modeling; 7th International Wo José Mira,José R. álvarez Conference proceedings 2003 Springer-Verlag Berlin

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1.4.2.4 The continental slope and rise,f is an intrinsic parameter of the model that can vary with a given set of rules. In this work we show that both the temporal activity and the encoded rhythms in an ensemble of cortical neurons depend on the topology of the network.

天空

Gnrh670

1.5 Sedimentation of the ocean bottom,rning algorithm. Then it details the RL_HNFB model, which is a hierarchical neuro-fuzzy system with reinforcement learning process. The RL_HNFB model was evaluated in a benchmark application - mountain car - yielding good performance when compared with different reinforcement learning models.

PAN

1.5 Sedimentation of the ocean bottom,e voltage changes along the neuron morphology. Strong axial gradients of potential arise that “isolate” the seized dendritic domains while leaving near regions capable to develop normal electrical activity.

材料等

1.4.2.7 Island arcs and trench systems,ory process as recategorization. Distinct experiences that share a common clement can be consolidated in the memory in a way such that they arc substrata for a new solution. The model is applied to an autobiographical robot.

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Life-long learning: consolidation of novel events into dynamic memory representationsory process as recategorization. Distinct experiences that share a common clement can be consolidated in the memory in a way such that they arc substrata for a new solution. The model is applied to an autobiographical robot.

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