{"id":1595,"date":"2014-10-28T17:02:54","date_gmt":"2014-10-28T16:02:54","guid":{"rendered":"https:\/\/project.inria.fr\/plasma-lab\/?page_id=1595"},"modified":"2015-04-22T10:55:08","modified_gmt":"2015-04-22T08:55:08","slug":"simple-chain","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/plasma-lab\/examples\/simple-chain\/","title":{"rendered":"Simple chain"},"content":{"rendered":"<p><\/p>\n<p style=\"text-align: justify;\">This model allows to experiment the <a title=\"Importance splitting\" href=\"https:\/\/project.inria.fr\/plasma-lab\/importance-splitting\/\">importance splitting algorithm<\/a>. The model consists in a single module that described a chain of <em>n<\/em> states. At each state it is either possible to continue to the next state with probability <em>p<\/em>, or to exit the chain with probability <em>1-p<\/em>. The property that we check determine the probability to reach the end of the chain. This probability can be easily computed as \\(p^n\\), where <em>n<\/em> is the length of the chain. The model can be easily configured to vary the results by changing the number of states or the probability <em>p<\/em>.<\/p>\n<p style=\"text-align: justify;\">The score function in this model corresponds to the state reached in the chain. For a chain of\u00a0 10 states, the observer that we use is therefore the following:<\/p>\n<p style=\"text-align: justify;\"><div class=\"alert alert-success\" role=\"alert\"><p class=\"printonly\"><strong>Important!<\/strong><\/p><\/p>\n<p style=\"text-align: justify;\" class=\"first-p\">observer chainObserver<br \/>\nscore : double init 0;<br \/>\ndecided : bool init false;<\/p>\n<p>[] s != 11 &amp; score &lt; s -&gt; (score&#8217;=score+1);<br \/>\n[] s&gt;=10 -&gt; (decided&#8217;=true);<br \/>\nendobserver<\/p>\n<p style=\"text-align: justify;\"><\/div><\/p>\n<p style=\"text-align: justify;\">The model file is available <a href=\"http:\/\/plasma-lab.gforge.inria.fr\/plasma_lab_examples\/Rare\/SimpleChain.plasma\"><strong>here<\/strong><\/a>.<\/p>\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>This model allows to experiment the importance splitting algorithm. The model consists in a single module that described a chain of n states. At each state it is either possible to continue to the next state with probability p, or to exit the chain with probability 1-p. The property that\u2026<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/plasma-lab\/examples\/simple-chain\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":235,"featured_media":0,"parent":236,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1595","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/plasma-lab\/wp-json\/wp\/v2\/pages\/1595","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/plasma-lab\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/plasma-lab\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/plasma-lab\/wp-json\/wp\/v2\/users\/235"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/plasma-lab\/wp-json\/wp\/v2\/comments?post=1595"}],"version-history":[{"count":12,"href":"https:\/\/project.inria.fr\/plasma-lab\/wp-json\/wp\/v2\/pages\/1595\/revisions"}],"predecessor-version":[{"id":2022,"href":"https:\/\/project.inria.fr\/plasma-lab\/wp-json\/wp\/v2\/pages\/1595\/revisions\/2022"}],"up":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/plasma-lab\/wp-json\/wp\/v2\/pages\/236"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/plasma-lab\/wp-json\/wp\/v2\/media?parent=1595"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}