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Optimal stopping for measure-valued piecewise deterministic Markov processes
| Content Provider | Scilit |
|---|---|
| Author | Cloez, Bertrand de Saporta, Benoîte Joubaud, Maud |
| Copyright Year | 2020 |
| Description | This paper investigates the random horizon optimal stopping problem for measure-valued piecewise deterministic Markov processes (PDMPs). This is motivated by population dynamics applications, when one wants to monitor some characteristics of the individuals in a small population. The population and its individual characteristics can be represented by a point measure. We first define a PDMP on a space of locally finite measures. Then we define a sequence of random horizon optimal stopping problems for such processes. We prove that the value function of the problems can be obtained by iterating some dynamic programming operator. Finally we prove via a simple counter-example that controlling the whole population is not equivalent to controlling a random lineage. |
| Related Links | https://www.cambridge.org/core/services/aop-cambridge-core/content/view/37EBBE16049A145A81A7DFBA8853B26F/S0021900220000182a.pdf/div-class-title-optimal-stopping-for-measure-valued-piecewise-deterministic-markov-processes-div.pdf |
| Ending Page | 512 |
| Page Count | 16 |
| Starting Page | 497 |
| ISSN | 00219002 |
| e-ISSN | 14756072 |
| DOI | 10.1017/jpr.2020.18 |
| Journal | Journal of applied probability |
| Issue Number | 2 |
| Volume Number | 57 |
| Language | English |
| Publisher | Cambridge University Press (CUP) |
| Publisher Date | 2020-06-01 |
| Access Restriction | Open |
| Subject Keyword | Journal of applied probability Applied Mathematics Markov Processes Measure Space Optimal Stopping Dynamic Programming Population Dynamics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Statistics and Probability Statistics, Probability and Uncertainty |
