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40 lines
1.1 KiB
40 lines
1.1 KiB
// self stabilisation algorithm Beauquier, Gradinariu and Johnen
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// gxn/dxp 18/07/02
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// model is an mdp
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nondeterministic
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// module of process 1
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module process1
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d1 : bool; // probabilistic variable
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p1 : bool; // deterministic variable
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[] (d1=d9) & (p1=p9) -> 0.5 : (d1'=!d1) & (p1'=p1) + 0.5 : (d1'=!d1) & (p1'=!p1);
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[] (d1=d9) & !(p1=p9) -> (d1'=!d1);
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endmodule
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// add further processes through renaming
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module process2 =process1[p1=p2 ,p9=p1, d1=d2 ,d9=d1] endmodule
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module process3 =process1[p1=p3 ,p9=p2, d1=d3 ,d9=d2] endmodule
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module process4 =process1[p1=p4 ,p9=p3, d1=d4 ,d9=d3] endmodule
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module process5 =process1[p1=p5 ,p9=p4, d1=d5 ,d9=d4] endmodule
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module process6 =process1[p1=p6 ,p9=p5, d1=d6 ,d9=d5] endmodule
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module process7 =process1[p1=p7 ,p9=p6, d1=d7 ,d9=d6] endmodule
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module process8 =process1[p1=p8 ,p9=p7, d1=d8 ,d9=d7] endmodule
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module process9 =process1[p1=p9 ,p9=p8, d1=d9 ,d9=d8] endmodule
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// cost in any state is 1 (expected number of steps)
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rewards
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true : 1;
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endrewards
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// initial states - any state with more than 1 token, that is all states
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init
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true
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endinit
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