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--- didattica:magistrale:atse:ay_1819:main [2019/06/04 17:03]
michele [General Information]
+++ didattica:magistrale:atse:ay_1819:main [2020/09/17 16:55] (current)
@@ Line 21: / Line 21: @@
 **Referenfes**:
-  * [[http://www.dcs.ed.ac.uk/pepa/tools/|PEPA]]
   * [[https://www.ic.unicamp.br/~wainer/cursos/1s2013/ml/livro.pdf|All of Statistics]]
   * [[https://drive.google.com/open?id=1f3gyaHLBv_xr1_5if7wX7ANt4L150-op|On hypothesis testing for statistical model checking]]
+**Tools**:
+  * [[http://www.dcs.ed.ac.uk/pepa/tools/|PEPA]]
   * [[https://repast.github.io|The Repast Suite]]
+  * [[http://homepages.inf.ed.ac.uk/jeh/Bio-PEPA/biopepa.html|Bio-PEPA]]
+  * [[https://github.com/quasylab/sibilla|Sibilla]]
 </WRAP>
@@ Line 64: / Line 69: @@
   * {{ :didattica:magistrale:atse:ay_1819:08slides.pdf |Slides 08: Statistics. }}
   * {{ :didattica:magistrale:atse:ay_1819:09slides.pdf |Slides 09: Statistical Inference. }}
-  * {{ :didattica:magistrale:atse:ay_1819:10slides.pdf |Sludes 19: Statistical Transient Analysis. }}
+  * {{ :didattica:magistrale:atse:ay_1819:10slides.pdf |Slides 10: Statistical Transient Analysis. }}
+  * {{ :didattica:magistrale:atse:ay_1819:11slides.pdf |Slides 11: Sibilla, a framework for agent simulation and analysis. }}
 **Lectures**
@@ Line 88: / Line 94: @@
   * Lecture 28/5/2019 ([[https://unicam.webex.com/recordingservice/sites/unicam/recording/playback/c6059aa32fc24394a31252cc364ccb98|Streaming]])
   * Lecture 30/5/2019 ([[https://unicam.webex.com/recordingservice/sites/unicam/recording/playback/fa4a7e28be514b9384b9929d16491a3a|Streaming]])
-  * Lecture 04/6/2019
+  * Lecture 04/6/2019 ([[https://unicam.webex.com/recordingservice/sites/unicam/recording/playback/1ddeeed5d4514c789acfea318015259f|Streaming]])
 </WRAP>
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 <WRAP box round center 95%>
 **Exam Dates**
-  * Will be published soon...
+  * The date is defined with the teacher.
+**Exam rules**: Each student selects **one** of the following topics and produces a short report (between 5 and 10 pages) that will be discussed at the exam:
+  * Use either [[https://github.com/quasylab/sibilla|Sibilla]] or one of the tools listed above to model a scenario. Examples of possible scenarios are:
+     * [[https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology|Epidemic Model]]
+     * [[http://www.prismmodelchecker.org/casestudies/virus.phpVirus|Diffusion Model]]
+     * [[https://en.wikipedia.org/wiki/Lotka–Volterra_equations|Predator-Prey Model]]
+     * [[http://www.prismmodelchecker.org/casestudies/asynchronous_leader.php|Asynchronous Leader Election]]
+     * [[http://www.prismmodelchecker.org/casestudies/crowds.php|Crowds protocol]]
+     * [[http://www.prismmodelchecker.org/casestudies/stable_matching.php|Stable matching]]
+     * ...
+  * Study one of the following topics:
+     * {{ :didattica:magistrale:atse:ay_1718:10.1007_s10009-014-0350-1.pdf |Statistical Model Checking}} (study the methods that was not considered in the lectures)
+     * [[https://arxiv.org/abs/1506.08234|Robust Online Monitoring of Signal Temporal Logic]]
+     * [[https://www.sciencedirect.com/science/article/pii/S0304397515002224?via%3Dihub| System design of stochastic models using robustness of temporal properties]]
+     * [[https://www.sciencedirect.com/science/article/pii/S0890540116000055?via%3Dihub| Smoothed model checking ]] (A technique for parameter optimisation)
+     * [[https://www.sciencedirect.com/science/article/pii/S0166531613000023?via%3Dihub| Continuous approximation of stochastic models]]
+  * A student can suggest a topic of her/his interest.
 </WRAP>