Learning to solve small instances of a problem should help in solving large instances. Unfortunately, most neural network architectures do not exhibit this form of scalability. Our...
Real world processes with an “intensity” and “direction” component can be made complex by convenience of representation (vector fields, radar, sonar), and their processin...
We believe that communication in multi-agent system has two major meanings. One of them is to transmit one agent's observed information to the other. The other meaning is to ...
Abstract. In [8] Yamauchi and Beer explored the abilities of continuous time recurrent neural networks (CTRNNs) to display reinforcementlearning like abilities. The investigated ta...
Abstract. This paper examines the generalization capability in learning multiple temporal patterns by the recurrent neural network with parametric bias (RNNPB). Our simulation expe...