TWEANN Approach to the Double Pole Balancing Problem
نویسندگان
چکیده
We discuss the effect of mutation probabilities on performance Mutation-Based Evolving Artificial Neural Networks (MBEANN), which is one methods Topology and Weight (TWEANN). TWEANN an approach for evolving both structures weights artificial neural networks. expected to perform well than using a fixed-topology network with only weight values. The phenotype MBEANN consists sub-networks, topology grows independently within them. Moreover, structural mutations are designed reduce influence fitness value. In this study, we focus by double pole balancing problem without velocity inputs. compared NeuroEvolution Augumenting Topologies (NEAT), typical method TWEANN. results show that has higher task achievement rate regardless difficulty. From comparison NEAT, shows even larger structure due sub-networks.
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ژورنال
عنوان ژورنال: Shisutemu Seigyo Jo?ho? Gakkai ronbunshi
سال: 2022
ISSN: ['1342-5668', '2185-811X']
DOI: https://doi.org/10.5687/iscie.35.126