Sotetsu Koyamada

collaborators

2 papers

cs.AI2020

Suphx: Mastering Mahjong with Deep Reinforcement Learning

Junjie Li, Sotetsu Koyamada, Qiwei Ye +7

Artificial Intelligence (AI) has achieved great success in many domains, and game AI is widely regarded as its beachhead since the dawn of AI. In recent years, studies on game AI h…

stat.ML2017

Neural Sequence Model Training via $α$ -divergence Minimization

Sotetsu Koyamada, Yuta Kikuchi, Atsunori Kanemura +2

We propose a new neural sequence model training method in which the objective function is defined by $α$ -divergence. We demonstrate that the objective function generalizes the maxi…

Suphx: Mastering Mahjong with Deep Reinforcement Learning

Neural Sequence Model Training via α-divergence Minimization

Neural Sequence Model Training via $α$ -divergence Minimization