- Associate Professor Masashi Aono
Introduction of the discussion
Eubacteria (Physarum polycephalum) is an amoeba-like unicellular organism, and when multiple feeds are placed around it, it transforms into a shape that connects all the feeds with the shortest path to maximize nutrient absorption.
This means that Eubacteria that do not have a centralized information processing system have the computational power to solve certain optimization problems in an autonomous decentralized manner.
In other words, Eubacteria can be regarded as massively parallel computing devices with advanced information processing capabilities that are self-organizing spatio-temporal vibration dynamics.
If the essence of Eubacteria dynamics can be extracted as an algorithm by exploring the superiority and applicability of this Eubacteria calculator, it can be applied to the development of software and hardware implemented as logic.
Finding the problem
In general, many methods for efficiently searching for an optimal solution from a large number of candidates utilize stochastic noise with no causal correlation in time series as fluctuations.
On the other hand, agents with dynamics operate while maintaining spatio-temporal correlation.
Then, what is the advantage of a search that uses fluctuations with spatio-temporal correlation derived from dynamics compared to a search that uses stochastic noise as fluctuations?
Associate professor Aono has developed a parallel search algorithm called “tug-of-war model” inspired by light phobic response dynamics of the Eubacteria branch and realized an efficient solution search.
By making AI learn deeply the Eubacteria algorithm and by deriving a decision-making strategy optimization algorithm that selects the best move in Go / Shogi and implement it in the execution environment, I would like to compare the algorithmic superiority with AI Go and AI Shogi that defeated professional players.
Examining the conclusion
By studying with Associate Professor Masashi Aono, who is a leading expert in natural computational algorithms using Physarum polycephalum, with extensive experience, I am sure that I could obtain various perspectives regarding my research and it would open up new horizons for me.
Therefore, I believe that Keio University’s Faculty of Environment and Information Studies is the most suitable place for pursuing my research and social contributions, and I am aspiring to enter your school and study in your laboratory.