Recent studies show that state-space dynamics of randomly initialized recurrent neural network (RNN) has interesting and potentially useful properties even without training. More p...
This paper presents our Recurrent Control Neural Network (RCNN), which is a model-based approach for a data-efficient modelling and control of reinforcement learning problems in di...
We explore a computationally efficient method of simulating realistic networks of neurons introduced by Knight, Manin, and Sirovich (1996) in which integrate-and-fire neurons are ...
Abstract. In the design of behavior-based control architectures for robots it is common to use biology as inspiration, and often the observed functionalities of insect behaviors ar...
—Robot imitation is a useful and promising alternative to robot programming. Robot imitation involves two crucial issues. The first is how a robot can imitate a human whose phys...
Ryunosuke Yokoya, Tetsuya Ogata, Jun Tani, Kazunor...