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A decision-theoretic approach to modeling the response of multi-strain pathogens to humoral defense is investigated in this paper. The reported theory of language-measure theoretic optimal control is used to compute the optimal response of the invading pathogen. The model is validated by comparison of simulation results with in-vivo observations and contrasted with prominent existing modeling approaches.
A novel path planning algorithm L* is introduced that reduces the problem to optimization of a probabilistic finite state machine and applies the rigorous theory of language-measure-theoretic optimal control to compute v-optimal paths to the specified goal. It is shown that although the underlying navigation model is probabilistic, the proposed algorithm computes plans that can be executed in a deterministic...
This paper modifies the signed real measure of regular languages, which has been reported in recent literature for analysis and synthesis of discrete event supervisory control laws. A new concept of renormalized measure is introduced to eliminate a user-selectable parameter in the present version of the language measure
The signed real measure of regular languages has been introduced and validated in recent literature for quantitative analysis and synthesis of discrete-event supervisory (DES) control systems. This paper reports several generalizations of the language measure, which are applicable to synthesis of optimal discrete event supervisory control. These generalizations eliminate a user-selectable parameter...
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