Presynaptic inhibition balances the trade-off between differential sensitivity and reproducibility. - Hiroyuki Ohta; Daisuke Uragami; Yasuhiro Nishida; James C. Houk (SCIS&ISIS, 2012)

Balancing between incremental learning and generalization by structured mutual inhibition: Shifting away from the question of whether there is a grandmother cell and toward conceptualization. - Daisuke Uragami; Hiroyuki Ohta (SCIS&ISIS, 2012)

Multilayered neural network with structural lateral inhibition for incremental learning and conceptualization. - Daisuke Uragami; Hiroyuki Ohta (Biosyst., 2014)

Cognitively inspired reinforcement learning architecture and its application to giant-swing motion control. - Daisuke Uragami; Tatsuji Takahashi; Yoshiki Matsuo (Biosyst., 2014)

Robotic action acquisition with cognitive biases in coarse-grained state space. - Daisuke Uragami; Yu Kohno; Tatsuji Takahashi (Biosyst., 2016)

Universal Emergence of 1/f Noise in Asynchronously Tuned Elementary Cellular Automata. - Daisuke Uragami; Yukio-Pegio Gunji (Complex Syst., 2018)

Breaking of the Trade-Off Principle between Computational Universality and Efficiency by Asynchronous Updating. - Yukio-Pegio Gunji; Daisuke Uragami (Entropy, 2020)

Computational Power of Asynchronously Tuned Automata Enhancing the Unfolded Edge of Chaos. - Yukio-Pegio Gunji; Daisuke Uragami (Entropy, 2021)

Universal Criticality in Reservoir Computing Using Asynchronous. - Daisuke Uragami; Yukio-Pegio Gunji (Complex Syst., 2022)

Social satisficing: Multi-agent reinforcement learning with satisficing agents. - Daisuke Uragami; Noriaki Sonota; Tatsuji Takahashi (Biosyst., 2024)