A Decision Transformer trained on human gameplay optimizes grain boundary networks, reaching about 92% of simulated annealing's solution quality with orders of magnitude fewer iterations and transferring across material models without retraining.
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A Decision Transformer Approach to Grain Boundary Network Optimization
A Decision Transformer trained on human gameplay optimizes grain boundary networks, reaching about 92% of simulated annealing's solution quality with orders of magnitude fewer iterations and transferring across material models without retraining.