— We present the memetic climber, a simple search algorithm that learns topology and weights of neural networks on different time scales. When applied to the problem of learning ...
In this paper we describe a model in which artificial evolution is employed to design neural mechanisms that control the motion of two autonomous robots required to communicate th...
Abstract. Artificial agents controlled by dynamic recurrent node networks with fixed weights are evolved to search for food and associate it with one of two different temperatur...
Abstract. In recent years simulation tools for agent-environment interactions have included increasingly complex and physically realistic conditions. These simulations pose challen...
One approach to optimal planning is to first start with a sub- optimal solution as a seed plan, and then iteratively search for shorter plans. This approach inevitably leads to an...