Abstract
The neuro-evolution is a domain of artificial intelligence which uses the evolutionary approach to produce artificial neural networks. There are many neuro-evolutionary methods and one of them is Assembler Encoding. This paper compares Assembler Encoding with other methods from the range of neuro-evolution and and reinforcement learning. During comparison tests, the task was to form neuro-controllers for three variants of the inverted pendulum problem. The variants differed in the amount of information supplied to each neuro-controller and in the number of poles installed on a cart.