A computer-implemented method of performing robot learning tasks comprising sensorimotor learning tasks, wherein the sensorimotor learning tasks comprise locomotion or grasping tasks, the method comprising processing inputs using a sequence of deep neural networks (DNNs), wherein each DNN in the sequence of DNNs has been trained to perform a respective robot learning task of a sequence of sensorimotor robot learning tasks consisting of locomotion or grasping tasks, the sequence of DNNs comprising: a first DNN that corresponds to a first robot learning task of the sequence of robot learning tasks, wherein (i) the first DNN comprises an input layer, an output layer, and a first plurality of indexed hidden layers, and (ii) each layer in the first plurality of indexed hidden layers is configured to receive a respective layer input and process the layer input to generate a respective layer output; and one or more subsequent DNNs (106, 108) corresponding to one or more subsequent respective robot learning tasks of the sequence of robot learning tasks, wherein each subsequent DNN in the sequence of DNNs is a DNN configured to perform a corresponding one of the subsequent sensorimotor robot learning tasks and (i) each subsequent DNN comprises a respective input layer, a respective output layer, and a respective plurality of indexed hidden layers, and (ii) each layer in a respective plurality of indexed hidden layers of said each subsequent DNN with index, i, greater than one receives input from (i) a preceding hidden layer of the respective subsequent DNN, and (ii) one or more preceding hidden layers of respective preceding DNNs, through respective non-linear lateral connections, wherein a preceding hidden layer is a layer whose index is one less than the index, i; the method further comprising: each DNN receiving a respective input as part of the locomotion or grasping sensorimotor robot learning task corresponding to that respective DNN in the sequence of DNNs; and processing the respective inputs using the respective DNNs of the sequence of DNNs, using the last subsequent DNN in the sequence to generate a last subsequent DNN output for performing the locomotion or grasping sensorimotor robot learning task corresponding to the last subsequent DNN. a first DNN that corresponds to a first robot learning task of the sequence of robot learning tasks, wherein (i) the first DNN comprises an input layer, an output layer, and a first plurality of indexed hidden layers, and (ii) each layer in the first plurality of indexed hidden layers is configured to receive a respective layer input and process the layer input to generate a respective layer output; and (i) the first DNN comprises an input layer, an output layer, and a first plurality of indexed hidden layers, and (ii) each layer in the first plurality of indexed hidden layers is configured to receive a respective layer input and process the layer input to generate a respective layer output; and one or more subsequent DNNs (106, 108) corresponding to one or more subsequent respective robot learning tasks of the sequence of robot learning tasks, wherein each subsequent DNN in the sequence of DNNs is a DNN configured to perform a corresponding one of the subsequent sensorimotor robot learning tasks and (i) each subsequent DNN comprises a respective input layer, a respective output layer, and a respective plurality of indexed hidden layers, and (ii) each layer in a respective plurality of indexed hidden layers of said each subsequent DNN with index, i, greater than one receives input from (i) a preceding hidden layer of the respective subsequent DNN, and (ii) one or more preceding hidden layers of respective preceding DNNs, through respective non-linear lateral connections, wherein a preceding hidden layer is a layer whose index is one less than the index, i; (i) each subsequent DNN comprises a respective input layer, a respective output layer, and a respective plurality of indexed hidden layers, and (ii) each layer in a respective plurality of indexed hidden layers of said each subsequent DNN with index, i, greater than one receives input from (i) a preceding hidden layer of the respective subsequent DNN, and (ii) one or more preceding hidden layers of respective preceding DNNs, through respective non-linear lateral connections, wherein a preceding hidden layer is a layer whose index is one less than the index, i; (i) a preceding hidden layer of the respective subsequent DNN, and (ii) one or more preceding hidden layers of respective preceding DNNs, through respective non-linear lateral connections, wherein a preceding hidden layer is a layer whose index is one less than the index, i; each DNN receiving a respective input as part of the locomotion or grasping sensorimotor robot learning task corresponding to that respective DNN in the sequence of DNNs; and processing the respective inputs using the respective DNNs of the sequence of DNNs, using the last subsequent DNN in the sequence to generate a last subsequent DNN output for performing the locomotion or grasping sensorimotor robot learning task corresponding to the last subsequent DNN.