PENERAPAN PEMBELAJARAN Q MENDALAM SEBAGAI ALGORITMA PEMBELARAJAN PENGUATAN UNTUK MELATIH AGEN PEMAIN GOMOKU

• Main Author: Nugraha Jiun, Anang
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/85587
• Institution: Institut Teknologi Bandung

Artificial intelligence is developing very quickly. One method to develop artificial intelligence is reinforcement learning. Through reinforcement learning, an agent learns through interaction with its environment. This method can be used for many things from teaching a robot to walk to creating an artificial intelligence that can play chess at a high skill level. This research was conducted to see if one reinforcement learning algorithm, Deep Q Learning, could be used to train an artificial intelligence to play a traditional board game from Japan called Gomoku. Gomoku is a game that is very similar with Tictac- toe and uses a 15x15 board. It was found that Deep Q Learning can produce an artificial intelligence that has a very basic strategy for Gomoku for a relatively small amount of training time.