CartesianFusion

This openEnv is a prototype where the stellarator community can look at it as a reference for how to build a RL env for stellarator parameters optimization. Some experts in the industry use a 'black-box' optimizer to tune the parameters. Sometimes that optimizer can hit a ceiling. This env has a definite verifier (a PDE solver) and a reward system aimed to push the boundary. From my limited research, there's not been a RL paper on stellarator optimization. Fortunately, the trained model performed better than the baseline. Our reward works like a game score for reactor design: it first gives points for fixing the design until it satisfies all the required physics rules, where P1 feasibility is just a “how far from valid” number and 0 means the design finally meets every rule. Once the design is valid, the reward shifts to giving points for making it better, while subtracting points for wasting moves, getting stuck in loops, or ending with a weak result.

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