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Optimal Control Strategies For Complex Biological Systems, Afroza Shirin
Optimal Control Strategies For Complex Biological Systems, Afroza Shirin
Mechanical Engineering ETDs
To better understand and to improve therapies for complex diseases such as cancer or diabetes, it is not sufficient to identify and characterize the interactions between molecules and pathways in complex biological systems, such as cells, tissues, and the human body. It also is necessary to characterize the response of a biological system to externally supplied agents (e.g., drugs, insulin), including a proper scheduling of these drugs, and drug combinations in multi drugs therapies. This obviously becomes important in applications which involve control of physiological processes, such as controlling the number of autophagosome vesicles in a cell, or regulating the …
Verification Of Stochastic Reach-Avoid Using Rkhs Embeddings, Adam J. Thorpe
Verification Of Stochastic Reach-Avoid Using Rkhs Embeddings, Adam J. Thorpe
Electrical and Computer Engineering ETDs
A solution to the terminal-hitting and first-hitting stochastic reach-avoid problem for a Markov control process is presented. This solution takes advantage of a nonparametric representation of the stochastic kernel as a conditional distribution embedding within a reproducing kernel Hilbert space (RKHS). Because the disturbance is modeled as a data-driven stochastic process, this representation avoids intractable integrals in the dynamic recursion of the reach-avoid problem since the expectations can be calculated as an inner product within the RKHS. An example using a high-dimensional chain of integrators is presented, as well as for Clohessy-Wiltshire-Hill (CWH) dynamics.