6 papers
Acceleration of Evolutionary Processes by Learning and Extended Fisher's Fundamental Theorem
So Nakashima, Tetsuya J. Kobayashi
Natural selection is general and powerful concept not only to explain evolutionary processes of biological organisms but also to design engineering systems such as genetic algorith…
Forward and Backward Bellman equations improve the efficiency of EM algorithm for DEC-POMDP
Takehiro Tottori, Tetsuya J. Kobayashi
Decentralized partially observable Markov decision process (DEC-POMDP) models sequential decision making problems by a team of agents. Since the planning of DEC-POMDP can be interp…
Understanding how T helper cells learn to coordinate effective immune responses through the lens of reinforcement learning
Takuya Kato, Tetsuya J. Kobayashi
The adaptive immune system of vertebrates can detect, respond to, and memorize diverse pathogens from past experience. While the clonal selection of T helper (Th) cells is the simp…
Lineage EM Algorithm for Inferring Latent States from Cellular Lineage Trees
So Nakashima, Yuki Sughiyama, Tetsuya J. Kobayashi
Phenotypic variability in a population of cells can work as the bet-hedging of the cells under an unpredictably changing environment, the typical example of which is the bacterial…
Fitness response relation of a multi-type age-structured population dynamics
Yuki Sughiyama, So Nakashima, Tetsuya J. Kobayashi
We construct a pathwise formulation for a multi-type age-structured population dynamics, which involves an age-dependent cell replication and transition of gene- or phenotypes. By…
Individual Sensing can Gain more Fitness than its Information
Tetsuya J. Kobayashi, Yuki Sughiyama
Mutual information and its causal variant, directed information, have been widely used to quantitatively characterize the performance of biological sensing and information transduc…