7 citations · 11 across the 11 of their papers we have counts for
11 papers
Accelerating Evolutionary Strategy via Rao-Blackwellizing Realization of Uncertain Input
So Nakashima, Tetsuya J. Kobayashi
We investigate Optimization under Input Uncertainty (OIU), in which the input to the objective function, rather than the objective function itself, is subject to uncertainty. OIU a…
Convex Analysis of Relaxation Dynamics in Chemical Reaction Networks and Generalized Gradient Flows
Keisuke Sugie, Dimitri Loutchko, Tetsuya J. Kobayashi
We obtain bounds on the Kullback--Leibler divergence to equilibrium for mass-action chemical reaction networks (CRNs) with equilibrium. The associated trajectory-dependent bounds a…
Information geometry of perturbed gradient flow systems on hypergraphs: A perspective towards nonequilibrium physics
Dimitri Loutchko, Keisuke Sugie, Tetsuya J Kobayashi
This article serves to concisely review the link between gradient flow systems on hypergraphs and information geometry which has been established within the last five years. Gradie…
Information geometry of chemical reaction networks: Cramer-Rao bound and absolute sensitivity revisited
Dimitri Loutchko, Yuki Sughiyama, Tetsuya J. Kobayashi
Information geometry is based on classical Legendre duality but allows to incorporate additional structure such as algebraic constraints and Bregman divergence functions. It is nat…
Ancestral Reinforcement Learning: Unifying Zeroth-Order Optimization and Genetic Algorithms for Reinforcement Learning
So Nakashima, Tetsuya J. Kobayashi
Reinforcement Learning (RL) offers a fundamental framework for discovering optimal action strategies through interactions within unknown environments. Recent advancement have shown…
Optimality theory of stigmergic collective information processing by chemotactic cells
Masaki Kato, Tetsuya J. Kobayashi
Collective information processing is fundamental in various biological systems, where the cooperation of multiple cells results in complex functions beyond individual capabilities.…
Gradient sensing limit of a cell when controlling the elongating direction
Kento Nakamura, Tetsuya J. Kobayashi
Eukaryotic cells perform chemotaxis by determining the direction of chemical gradients based on stochastic sensing of concentrations at the cell surface. To examine the efficiency…
Transitions and Thermodynamics on Species Graphs of Chemical Reaction Networks
Keisuke Sugie, Dimitri Loutchko, Tetsuya J. Kobayashi
Chemical reaction networks (CRNs) exhibit complex dynamics governed by their underlying network structure. In this paper, we propose a novel approach to study the dynamics of CRNs…
Cramer-Rao bound and absolute sensitivity in chemical reaction networks
Dimitri Loutchko, Yuki Sughiyama, Tetsuya J. Kobayashi
Chemical reaction networks (CRN) comprise an important class of models to understand biological functions such as cellular information processing, the robustness and control of met…
Thermodynamic and Stoichiometric Laws Ruling the Fates of Growing Systems
Atsushi Kamimura, Yuki Sughiyama, Tetsuya J. Kobayashi
We delve into growing open chemical reaction systems (CRSs) characterized by autocatalytic reactions within a variable volume, which changes in response to these reactions. Underst…
Information geometric bound on general chemical reaction networks
Tsuyoshi Mizohata, Tetsuya J. Kobayashi, Louis-S. Bouchard +1
We investigate the dynamics of chemical reaction networks (CRNs) with the goal of deriving an upper bound on their reaction rates. This task is challenging due to the nonlinear nat…