Analysis, Combination and Integration of Neuroevolution and Backpropagation Algorithms for Gaming Environment
Andrei Darii, Maximilian Moll, Marian Sorin Nistor, Stefan Pickl, Ovidiu Constantin Novac, Cornelia Mihaela Novac, Ioan Mircea Gordan, Cornelia Emilia Gordan · 2023
This paper provides a method of combining Neu-roevolution with Backpropagation to achieve lower training times than Neuroevolution when training agents in a video game environment. The combination of these algorithms is reproduced by an alteration of the step of creating a new generation from the most capable agents with the creation of a new generation through the Backpropagation method using the preventively saved data of the most capable agent from the environment. Thus, for the new generation, a Neural Network trained with backpropagation is assigned instead of the best-performing Neural Network from the previous generation. As a result, the Neuroevolution with the Backpropagation method shows better performance when increasing the target of the environmental performance of the agent.