Individual #5’s action ratio, position states. by Larasmoyo Nugroho (18078260)

Performance comparison of four optimization methods. by Xuexing Du (20624042)

Block diagram of 2-DOF PIDA controller. by Erdal Eker (19251018)

“…The controller structure allows independent tuning of set-point tracking and disturbance rejection by introducing separate feedforward paths in the proportional and derivative channels while maintaining integral and acceleration actions on the error signal. To optimize the controller parameters, the recently developed greater cane rat algorithm (GCRA) is employed for the first time in this context. …”

Zoomed view of Fig 7. by Erdal Eker (19251018)

“…The controller structure allows independent tuning of set-point tracking and disturbance rejection by introducing separate feedforward paths in the proportional and derivative channels while maintaining integral and acceleration actions on the error signal. To optimize the controller parameters, the recently developed greater cane rat algorithm (GCRA) is employed for the first time in this context. …”

Zoomed view of Fig 10. by Erdal Eker (19251018)

“…The controller structure allows independent tuning of set-point tracking and disturbance rejection by introducing separate feedforward paths in the proportional and derivative channels while maintaining integral and acceleration actions on the error signal. To optimize the controller parameters, the recently developed greater cane rat algorithm (GCRA) is employed for the first time in this context. …”

DataSheet1_Computational design of custom therapeutic cells to correct failing human cardiomyocytes.pdf by Andrew Tieu (14441499)

“…</p><p>Methods: Candidate custom cells were simulated with a combination of ion channels from non-excitable cells and healthy human cardiomyocytes (hCMs). Using a genetic algorithm-based optimization approach, candidate cells were accepted if a root mean square error (RMSE) of less than 50% relative to healthy hCM was achieved for both action potential and calcium transient waveforms for the cell-treated HF cardiomyocyte, normalized to the untreated HF cardiomyocyte.…”

DataSheet1_Computational design of custom therapeutic cells to correct failing human cardiomyocytes.pdf by Andrew Tieu (14441499)

“…</p><p>Methods: Candidate custom cells were simulated with a combination of ion channels from non-excitable cells and healthy human cardiomyocytes (hCMs). Using a genetic algorithm-based optimization approach, candidate cells were accepted if a root mean square error (RMSE) of less than 50% relative to healthy hCM was achieved for both action potential and calcium transient waveforms for the cell-treated HF cardiomyocyte, normalized to the untreated HF cardiomyocyte.…”

Data_Sheet_1_How Morphological Computation Shapes Integrated Information in Embodied Agents.PDF by Carlotta Langer (11764325)

“…There, we calculate the optimal policy for goal-directed behavior based on the “planning as inference” method, in which the information-geometric em-algorithm is used to optimize the likelihood of the goal. …”