Published 2024
“…In this study, we explore the integration of Generative Adversarial Networks (GANs) and Deep Reinforcement Learning (DRL) methods, focusing on the performance comparison between different architectures of Sequence Generative Adversarial Networks (SeqGAN) and policy gradient
algorithms. We address key challenges in text generation, such as maintaining narrative coherence over long sequences, reducing text repetition, and
optimizing SeqGAN for diverse textual outputs. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis