This paper investigates possible connection strategies in sparsely connected associative memory models. This is interesting because real neural networks must have both efficient p...
This paper presents a feasibility study of evolutionary scheduling for gas pipeline operations. The problem is complex because of several constraints that must be taken into consi...
AbstractThis paper describes the evolution of controllers for racing a simulated radio-controlled car around a track, modelled on a real physical track. Five different controller a...
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...