Wulfram Gerstner
We study spatial learning and navigation for autonomous agents. A state space representation is constructed by unsupervised Hebbian learning during exploration. As a result of learning, a representation of the continuous two-dimensional (2-D) manifold in t ...
Institute of Electrical and Electronics Engineers2004