int snc_size = .layers.SNc.units.size; float k = 1.0*.processes.Train_Prob.init_procs[3].s_args[0]/.layers.SNc.n_units; UnitSpec* us = .specs.FixedBiasUnitSpec.LearnBiasUnitSpec.matrisom_unitspec; int max_monval = .processes.Cycle_Prob.final_stats.size; int j; for (j=0;j0)&&(owner[0].se.val<0.5)) { int i; for (i=0;i act1) { owner.owner.cur_event.patterns[3].value[0] = 1.0; owner.owner.cur_event.patterns[3].value[1] = 0; owner.owner.cur_event.patterns[3].value[2] = 1.0; owner.owner.cur_event.patterns[3].value[3] = 0; } if (act1 > act0) { owner.owner.cur_event.patterns[3].value[0] = 0; owner.owner.cur_event.patterns[3].value[1] = 1.0; owner.owner.cur_event.patterns[3].value[2] = 0; owner.owner.cur_event.patterns[3].value[3] = 1.0; } GetMyTrialProc().SetCurLrate();