Hayato Dan

Title: Hayato Dan: Inventor in Multi-Agent Reinforcement Learning

Introduction

Hayato Dan is an inventor associated with Fujitsu Corporation in Yokohama, Japan. His patent work addresses multi-agent reinforcement learning, including how agents update policy parameters while accounting for individual and system-wide constraints.

Latest Patents

Dan is named on 1 patent: “Computer-readable recording medium storing multi-agent reinforcement learning program, information processing apparatus, and multi-agent reinforcement learning method.” The invention describes a process that follows a predetermined order for updating each agent’s policy parameter. It evaluates the parameter’s influence on a constraint specific to one agent and on a system-wide constraint, while sharing the effects of earlier updates. When the proposed update width falls within ranges determined by both influences, the process updates the parameter and shares its system-wide effect with the next agent in the order.

Career Highlights

Dan’s listed patent connects his work with Fujitsu’s information-processing and artificial-intelligence research. It focuses on coordinating policy updates across multiple agents while considering constraints at both the individual and system levels.

Collaborations

Yoshihiro Okawa and Natsuki Ishikawa are identified as Dan’s coworkers. The available information does not specify their roles in the patent or whether they collaborated on this invention.

Conclusion

Hayato Dan’s patent describes a structured approach to multi-agent reinforcement learning that accounts for shared system constraints as agents update their policies.