Abstract. In developing algorithms that dynamically changes the structure and weights of ANN (Artificial Neural Networks), there must be a proper balance between network complexit...
Results are presented of a simulation which mimics an evolutionary learning process for small networks. Special features of these networks include a high recurrency, a transition ...
Packet switching in connection-oriented networks that may have multiple parallel links between pairs of switches is considered. An e cient packet-scheduling algorithm that guarant...
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...
—This study proposes to generalize Hebbian learning by identifying and synchronizing the dynamical regimes of individual nodes in a recurrent network. The connection weights are ...