Applying interpolation-constrained autoencoders to world models approach reinforcement learning

• 主要作者: Kevin Winata
• 其他作者: Zinovi Rabinovich
• 格式: Final Year Project
• 語言: English
• 出版: Nanyang Technological University 2021
• 主題: Engineering::Computer science and engineering
• 在線閱讀: https://hdl.handle.net/10356/148004
• 機構: Nanyang Technological University

World Models Approach Reinforcement Learning helps to tackle complex problems by breaking down the learning task to Vision Model, Memory Model, and Controller Model. Variational Autoencoder (VAE) is commonly used for Vision Model. However, there has been development of other variants of Autoencoders...