Transfer learning through policy abstraction using learning vector quantization

• Main Authors: Ahmad Afif, Mohd Faudzi, Takano, Hirotaka, Murata, Jun'ichi
• Format: Article
• Language: English
• Published: UTeM 2018
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/21033/1/Transfer%20learning%20through%20policy%20abstraction.pdf; http://umpir.ump.edu.my/id/eprint/21033/; http://journal.utem.edu.my/index.php/jtec/article/view/3505/2453
• Institution: Universiti Malaysia Pahang Al-Sultan Abdullah

Reinforcement learning (RL) enables an agent to find a solution to a problem by interacting with the environment. However, the learning process always starts from scratch and possibly takes a long time. Here, knowledge transfer between tasks is considered. In this paper, we argue that an abstraction...