Working Memory Graphs
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['Model Image', 'WMG factored', 'nr-WMG factored', 'GRU factored', 'WMG flat', 'GRU flat']
To evaluate WMG’s sensitivity to hyperparameter selection, we applied the tuned hyperparameter settings from Level 4 to new training runs on all other levels. In particular, when the hyperparameter values tuned on Level 4 are used in Level 5 training runs, none of the models reach a 99% solution rate within 1 million training steps, but WMG with factored observations reaches higher levels of performance than the other models. Broadly, these results indicate that WMG is no more sensitive to hyperparameter settings than the baseline agents.