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// self stabilisation algorithm Beauquier, Gradinariu and Johnen
// gxn/dxp 18/07/02
// model is an mdp
nondeterministic
// module of process 1
module process1
d1 : bool; // probabilistic variable
p1 : bool; // deterministic variable
[] (d1=d11) & (p1=p11) -> 0.5 : (d1'=!d1) & (p1'=p1) + 0.5 : (d1'=!d1) & (p1'=!p1);
[] (d1=d11) & !(p1=p11) -> (d1'=!d1);
endmodule
// add further processes through renaming
module process2 =process1[p1=p2 ,p11=p1, d1=d2 ,d11=d1] endmodule
module process3 =process1[p1=p3 ,p11=p2, d1=d3 ,d11=d2] endmodule
module process4 =process1[p1=p4 ,p11=p3, d1=d4 ,d11=d3] endmodule
module process5 =process1[p1=p5 ,p11=p4, d1=d5 ,d11=d4] endmodule
module process6 =process1[p1=p6 ,p11=p5, d1=d6 ,d11=d5] endmodule
module process7 =process1[p1=p7 ,p11=p6, d1=d7 ,d11=d6] endmodule
module process8 =process1[p1=p8 ,p11=p7, d1=d8 ,d11=d7] endmodule
module process9 =process1[p1=p9 ,p11=p8, d1=d9 ,d11=d8] endmodule
module process10=process1[p1=p10,p11=p9, d1=d10,d11=d9] endmodule
module process11=process1[p1=p11,p11=p10,d1=d11,d11=d10] endmodule
// cost in any state is 1 (expected number of steps)
rewards
true : 1;
endrewards
// initial states - any state with more than 1 token, that is all states
init
true
endinit