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Decision procedure based discovery of rare behaviors in stochastic differential equation models of biological systems.
| Content Provider | CiteSeerX |
|---|---|
| Author | Ghosh, Arup K. Hussain, Faraz Jha, Sumit K. Langmead, Christopher J. Jha, Susmit |
| Abstract | Abstract—Stochastic Differential Equation (SDE) models are often used to model the dynamics of complex biological systems. The stochastic nature of these models means that some behaviors are more likely than others. It is often the case that a model’s primary purpose is to study rare but interesting or important behaviors, such as the formation of a tumor, or the failure of a cyber-physical system. Unfortunately, due to the limited availability of analytic methods for SDEs, stochastic simulations are the most common means for estimating (or bounding) the probability of rare behaviors. Naturally, the cost of stochastic simulations increases with the rarity of the behavior under consideration. To address this problem, we introduce a new algorithm, RESERCHE, that is specifically designed to quantify the likelihood of rare but interesting behaviors in SDE models. Our approach relies on the use |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Rare Behavior Decision Procedure Stochastic Differential Equation Model Biological System Stochastic Simulation Approach Relies Important Behavior Limited Availability Interesting Behavior Common Mean Abstract Stochastic Differential Equation Sde Model Model Primary Purpose Cyber-physical System New Algorithm Complex Biological System Stochastic Nature Analytic Method |
| Content Type | Text |
